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ORCIDKristian Kersting
Person information
- affiliation: TU Darmstadt, Computer Science Department, Germany
- affiliation: TU Darmstadt, Centre for Cognitive Science, Germany
- affiliation: TU Dortmund, Department of Computer Science, Germany
- affiliation: University of Bonn, Faculty of Agriculture, Germany
- affiliation: Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin, Germany
- affiliation: Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory (CSAIL), Cambridge, MA, USA
- affiliation (PhD 2005): University of Freiburg, Machine Learning Laborator, Germany
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Books and Theses
- 2016
[b3]Luc De Raedt
, Kristian Kersting, Sriraam Natarajan, David Poole:
Statistical Relational Artificial Intelligence: Logic, Probability, and Computation. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2016, ISBN 978-3-031-00022-5- 2014
- [b2]Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude W. Shavlik:
Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine. Springer Briefs in Computer Science, Springer 2014, ISBN 978-3-319-13643-1, pp. 1-68 - 2005
- [b1]Kristian Kersting:
An Inductive Logic Programming Approach to Statistical Relational Learning. University of Freiburg, Germany, Frontiers in Artificial Intelligence and Applications 148, IOS Press 2005, ISBN 978-1-58603-674-4, pp. 1-228
Journal Articles
- 2024
- [j73]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Structural causal models reveal confounder bias in linear program modelling. Mach. Learn. 113(3): 1329-1349 (2024) - [j72]Daniel Ochs, Karsten Wiertz, Sebastian Bußmann, Kristian Kersting, Devendra Singh Dhami:
Effective Risk Detection for Natural Gas Pipelines Using Low-Resolution Satellite Images. Remote. Sens. 16(2): 266 (2024) - 2023
- [j71]Nicolas Pfeuffer, Lorenz Baum, Wolfgang Stammer, Benjamin M. Abdel-Karim, Patrick Schramowski, Andreas M. Bucher, Christian Hügel, Gernot Rohde, Kristian Kersting, Oliver Hinz:
Explanatory Interactive Machine Learning. Bus. Inf. Syst. Eng. 65(6): 677-701 (2023) - [j70]Jannis Blüml, Johannes Czech, Kristian Kersting:
AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong. Frontiers Artif. Intell. 6 (2023) - [j69]Siwen Yan, Phillip Odom, Rahul Pasunuri, Kristian Kersting, Sriraam Natarajan:
Learning with privileged and sensitive information: a gradient-boosting approach. Frontiers Artif. Intell. 6 (2023) - [j68]Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Scalable Neural-Probabilistic Answer Set Programming. J. Artif. Intell. Res. 78: 579-617 (2023) - [j67]Lukas Struppek, Dominik Hintersdorf, Felix Friedrich, Manuel Brack, Patrick Schramowski, Kristian Kersting:
Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis. J. Artif. Intell. Res. 78: 1017-1068 (2023) - [j66]Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
αILP: thinking visual scenes as differentiable logic programs. Mach. Learn. 112(5): 1465-1497 (2023) - [j65]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
A typology for exploring the mitigation of shortcut behaviour. Nat. Mac. Intell. 5(3): 319-330 (2023) - 2022
- [j64]Parisa Kordjamshidi, Dan Roth, Kristian Kersting:
Declarative Learning-Based Programming as an Interface to AI Systems. Frontiers Artif. Intell. 5: 755361 (2022) - [j63]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. 140: 298-313 (2022) - [j62]Matej Petkovic, Michelangelo Ceci, Gianvito Pio, Blaz Skrlj, Kristian Kersting, Saso Dzeroski:
Relational tree ensembles and feature rankings. Knowl. Based Syst. 251: 109254 (2022) - [j61]Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf, Kristian Kersting:
Large pre-trained language models contain human-like biases of what is right and wrong to do. Nat. Mach. Intell. 4(3): 258-268 (2022) - [j60]Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer, Tim Grube, Kristian Kersting, Max Mühlhäuser:
User-Level Label Leakage from Gradients in Federated Learning. Proc. Priv. Enhancing Technol. 2022(2): 227-244 (2022) - 2021
- [j59]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure learning for relational logistic regression: an ensemble approach. Data Min. Knowl. Discov. 35(5): 2089-2111 (2021) - [j58]Niyati Rawal, Dorothea Koert, Cigdem Turan, Kristian Kersting, Jan Peters, Ruth Stock-Homburg:
ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition. Frontiers Robotics AI 8: 730317 (2021) - [j57]Plinio Moreno, Alexandre Bernardino, José Santos-Victor, Rodrigo M. M. Ventura, Kristian Kersting:
Editorial: Robots that Learn and Reason: Towards Learning Logic Rules from Noisy Data. Frontiers Robotics AI 8: 755933 (2021) - [j56]Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer:
Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation. Frontiers Artif. Intell. 4: 642263 (2021) - 2020
- [j55]Xiaoting Shao, Tjitze Rienstra, Matthias Thimm, Kristian Kersting:
Towards Understanding and Arguing with Classifiers: Recent Progress. Datenbank-Spektrum 20(2): 171-180 (2020) - [j54]Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz:
Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data. Frontiers Artif. Intell. 3: 24 (2020) - [j53]Patrick Schramowski, Cigdem Turan, Sophie F. Jentzsch, Constantin A. Rothkopf, Kristian Kersting:
The Moral Choice Machine. Frontiers Artif. Intell. 3: 36 (2020) - [j52]Rudolf Lioutikov, Guilherme Maeda, Filipe Veiga, Kristian Kersting, Jan Peters:
Learning attribute grammars for movement primitive sequencing. Int. J. Robotics Res. 39(1) (2020) - [j51]Rafet Sifa, Raheel Yawar, Rajkumar Ramamurthy, Christian Bauckhage, Kristian Kersting:
Matrix- and Tensor Factorization for Game Content Recommendation. Künstliche Intell. 34(1): 57-67 (2020) - [j50]Kristian Kersting:
Rethinking Computer Science Through AI. Künstliche Intell. 34(4): 435-437 (2020) - [j49]Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Franziska Herbert, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting:
Making deep neural networks right for the right scientific reasons by interacting with their explanations. Nat. Mach. Intell. 2(8): 476-486 (2020) - [j48]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig:
DeepDB: Learn from Data, not from Queries! Proc. VLDB Endow. 13(7): 992-1005 (2020) - 2019
- [j47]Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt:
Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach. Auton. Robots 43(6): 1393-1418 (2019) - [j46]Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel:
A unifying view of explicit and implicit feature maps of graph kernels. Data Min. Knowl. Discov. 33(6): 1505-1547 (2019) - [j45]Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni:
Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning. Frontiers Big Data 2: 52 (2019) - [j44]Fabrizio Riguzzi, Kristian Kersting, Marco Lippi, Sriraam Natarajan:
Editorial: Statistical Relational Artificial Intelligence. Frontiers Robotics AI 6: 68 (2019) - [j43]Anna Brugger, Jan Behmann, Stefan Paulus, Hans-Georg Luigs, Matheus Thomas Kuska, Patrick Schramowski, Kristian Kersting, Ulrike Steiner, Anne-Katrin Mahlein:
Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range. Remote. Sens. 11(12): 1401 (2019) - 2018
- [j42]Kristian Kersting:
Machine Learning and Artificial Intelligence: Two Fellow Travelers on the Quest for Intelligent Behavior in Machines. Frontiers Big Data 1: 6 (2018) - [j41]Kristian Kersting, Ulrich Meyer:
From Big Data to Big Artificial Intelligence? - Algorithmic Challenges and Opportunities of Big Data. Künstliche Intell. 32(1): 3-8 (2018) - [j40]Kristian Kersting:
Making AI Smarter. Künstliche Intell. 32(4): 227-229 (2018) - 2017
- [j39]Kristian Kersting, Martin Mladenov, Pavel Tokmakov:
Relational linear programming. Artif. Intell. 244: 188-216 (2017) - [j38]Mehul Bhatt, Kristian Kersting:
Semantic Interpretation of Multi-Modal Human-Behaviour Data - Making Sense of Events, Activities, Processes. Künstliche Intell. 31(4): 317-320 (2017) - [j37]Youness Dehbi, Fabian Hadiji, Gerhard Gröger, Kristian Kersting, Lutz Plümer:
Statistical Relational Learning of Grammar Rules for 3D Building Reconstruction. Trans. GIS 21(1): 134-150 (2017) - 2016
- [j36]Piotr Szymanski, Tomasz Kajdanowicz, Kristian Kersting:
How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification? Entropy 18(8): 282 (2016) - [j35]Christian Bauckhage, Kristian Kersting:
Collective Attention on the Web. Found. Trends Web Sci. 5(1-2): 1-136 (2016) - [j34]Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting:
Propagation kernels: efficient graph kernels from propagated information. Mach. Learn. 102(2): 209-245 (2016) - 2015
- [j33]Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang:
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36(1): 87-98 (2015) - [j32]Mirwaes Wahabzada, Stefan Paulus, Kristian Kersting, Anne-Katrin Mahlein:
Automated interpretation of 3D laserscanned point clouds for plant organ segmentation. BMC Bioinform. 16: 248:1-248:11 (2015) - [j31]Marion Neumann, Shan Huang, Daniel E. Marthaler, Kristian Kersting:
pyGPs: a Python library for Gaussian process regression and classification. J. Mach. Learn. Res. 16: 2611-2616 (2015) - [j30]Kristian Kersting, Sriraam Natarajan:
Statistical Relational Artificial Intelligence: From Distributions through Actions to Optimization. Künstliche Intell. 29(4): 363-368 (2015) - [j29]Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik:
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases. Mach. Learn. 100(1): 75-100 (2015) - [j28]Fabian Hadiji, Alejandro Molina, Sriraam Natarajan, Kristian Kersting:
Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data. Mach. Learn. 100(2-3): 477-507 (2015) - 2014
- [j27]Christian Bauckhage, Kristian Kersting, Christian Thurau:
Künstliche Intelligenz für Computerspiele - Historische Entwicklung und aktuelle Trends. Inform. Spektrum 37(6): 531-538 (2014) - [j26]Sriraam Natarajan, Baidya Nath Saha, Saket Joshi, Adam Edwards, Tushar Khot, Elizabeth M. Davenport, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian:
Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain. Int. J. Mach. Learn. Cybern. 5(5): 659-669 (2014) - 2013
- [j25]Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Dimitri Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar:
The AAAI-13 Conference Workshops. AI Mag. 34(4): 9- (2013) - [j24]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Data Min. Knowl. Discov. 27(3): 291-293 (2013) - [j23]Christian Bauckhage, Kristian Kersting:
Can Computers Learn from the Aesthetic Wisdom of the Crowd? Künstliche Intell. 27(1): 25-35 (2013) - [j22]Christian Bauckhage, Kristian Kersting:
Data Mining and Pattern Recognition in Agriculture. Künstliche Intell. 27(4): 313-324 (2013) - [j21]Babak Ahmadi, Kristian Kersting, Martin Mladenov, Sriraam Natarajan:
Exploiting symmetries for scaling loopy belief propagation and relational training. Mach. Learn. 92(1): 91-132 (2013) - [j20]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Mach. Learn. 93(1): 1-3 (2013) - 2012
- [j19]Christian Thurau, Kristian Kersting, Mirwaes Wahabzada, Christian Bauckhage:
Descriptive matrix factorization for sustainability Adopting the principle of opposites. Data Min. Knowl. Discov. 24(2): 325-354 (2012) - [j18]Tobias Lang, Marc Toussaint, Kristian Kersting:
Exploration in relational domains for model-based reinforcement learning. J. Mach. Learn. Res. 13: 3725-3768 (2012) - [j17]Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik:
Gradient-based boosting for statistical relational learning: The relational dependency network case. Mach. Learn. 86(1): 25-56 (2012) - [j16]Christian Bauckhage, Kristian Kersting, Albrecht Schmidt:
Agriculture's Technological Makeover. IEEE Pervasive Comput. 11(2): 4-7 (2012) - 2011
- [j15]Saket Joshi, Kristian Kersting, Roni Khardon:
Decision-theoretic planning with generalized first-order decision diagrams. Artif. Intell. 175(18): 2198-2222 (2011) - [j14]Albrecht Schmidt, Marc Langheinrich, Kristian Kersting:
Perception beyond the Here and Now. Computer 44(2): 86-88 (2011) - [j13]Christian Thurau, Kristian Kersting, Mirwaes Wahabzada, Christian Bauckhage:
Convex non-negative matrix factorization for massive datasets. Knowl. Inf. Syst. 29(2): 457-478 (2011) - [j12]Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan:
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Mach. Learn. 83(2): 133-135 (2011) - 2010
- [j11]David W. Aha, Mark S. Boddy, Vadim Bulitko, Artur S. d'Avila Garcez, Prashant Doshi, Stefan Edelkamp, Christopher W. Geib, Piotr J. Gmytrasiewicz, Robert P. Goldman, Pascal Hitzler, Charles L. Isbell Jr., Darsana P. Josyula, Leslie Pack Kaelbling, Kristian Kersting, Maithilee Kunda, Luís C. Lamb, Bhaskara Marthi, Keith McGreggor, Vivi Nastase, Gregory M. Provan, Anita Raja, Ashwin Ram, Mark O. Riedl, Stuart Russell, Ashish Sabharwal, Jan-Georg Smaus, Gita Sukthankar, Karl Tuyls, Ron van der Meyden, Alon Y. Halevy, Lilyana Mihalkova, Sriraam Natarajan:
Reports of the AAAI 2010 Conference Workshops. AI Mag. 31(4): 95-108 (2010) - 2009
- [j10]Christian Plagemann, Sebastian Mischke, Sam Prentice, Kristian Kersting, Nicholas Roy, Wolfram Burgard:
A Bayesian regression approach to terrain mapping and an application to legged robot locomotion. J. Field Robotics 26(10): 789-811 (2009) - 2008
- [j9]Manfred Jaeger, Lise Getoor, Kristian Kersting:
Preface. Ann. Math. Artif. Intell. 54(1-3): 1-2 (2008) - [j8]Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen:
Compressing probabilistic Prolog programs. Mach. Learn. 70(2-3): 151-168 (2008) - 2007
- [j7]Kristian Kersting, Christian Plagemann, Alexandru Cocora, Wolfram Burgard, Luc De Raedt:
Learning to transfer optimal navigation policies. Adv. Robotics 21(13): 1565-1582 (2007) - [j6]Niels Landwehr, Kristian Kersting, Luc De Raedt:
Integrating Naïve Bayes and FOIL. J. Mach. Learn. Res. 8: 481-507 (2007) - 2006
- [j5]Kristian Kersting:
An inductive logic programming approach to statistical relational learning. AI Commun. 19(4): 389-390 (2006) - [j4]Kristian Kersting, Luc De Raedt, Tapani Raiko:
Logical Hidden Markov Models. J. Artif. Intell. Res. 25: 425-456 (2006) - [j3]Alexandru Cocora, Kristian Kersting, Wolfram Burgard, Luc De Raedt, Christian Plagemann:
Learning Relational Navigation Policies. Künstliche Intell. 20(3): 12-18 (2006) - 2003
- [j2]Luc De Raedt, Kristian Kersting:
Probabilistic logic learning. SIGKDD Explor. 5(1): 31-48 (2003) - 2002
- [j1]Steven Ganzert, Josef Guttmann, Kristian Kersting, Ralf Kuhlen, Christian Putensen, Michael Sydow, Stefan Kramer:
Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning. Artif. Intell. Medicine 26(1-2): 69-86 (2002)
Conference and Workshop Papers
- 2023
- [c221]Sriraam Natarajan, Kristian Kersting:
Never Ending Reasoning and Learning: Opportunities and Challenges. AAAI Bridge Program 2023: 71-74 - [c220]Katharina Hämmerl, Björn Deiseroth, Patrick Schramowski, Jindrich Libovický, Constantin A. Rothkopf, Alexander Fraser, Kristian Kersting:
Speaking Multiple Languages Affects the Moral Bias of Language Models. ACL (Findings) 2023: 2137-2156 - [c219]Nandini Ramanan, Phillip Odom, Kristian Kersting, Sriraam Natarajan:
Active Feature Acquisition via Human Interaction in Relational domains. COMAD/CODS 2023: 70-78 - [c218]Patrick Schramowski, Manuel Brack, Björn Deiseroth, Kristian Kersting:
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models. CVPR 2023: 22522-22531 - [c217]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Revision Transformers: Instructing Language Models to Change Their Values. ECAI 2023: 756-763 - [c216]Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis. ICCV 2023: 4561-4573 - [c215]Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth:
Vision Relation Transformer for Unbiased Scene Graph Generation. ICCV 2023: 21825-21836 - [c214]Felix Friedrich, David Steinmann, Kristian Kersting:
One Explanation Does Not Fit XIL. Tiny Papers @ ICLR 2023 - [c213]Manuel Brack, Patrick Schramowski, Björn Deiseroth, Kristian Kersting:
ILLUME: Rationalizing Vision-Language Models through Human Interactions. ICML 2023: 3021-3037 - [c212]Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting:
Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Programs. ITSC 2023: 1506-1513 - [c211]Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami:
Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes. NeSy 2023: 103-117 - [c210]Zhongjie Yu, Martin Trapp, Kristian Kersting:
Characteristic Circuits. NeurIPS 2023 - [c209]Marco Bellagente, Manuel Brack, Hannah Teufel, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert Baldock, Souradeep Nanda, Koen Oostermeijer, Andrés Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach:
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation. NeurIPS 2023 - [c208]Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting:
SEGA: Instructing Text-to-Image Models using Semantic Guidance. NeurIPS 2023 - [c207]Björn Deiseroth, Mayukh Deb, Samuel Weinbach, Manuel Brack, Patrick Schramowski, Kristian Kersting:
ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation. NeurIPS 2023 - [c206]Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. NeurIPS 2023 - [c205]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Do Not Marginalize Mechanisms, Rather Consolidate! NeurIPS 2023 - [c204]Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbacher, Dwarak Vittal, Kristian Kersting:
Boosting Object Representation Learning via Motion and Object Continuity. ECML/PKDD (4) 2023: 610-628 - [c203]Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan:
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference. UAI 2023: 1964-1973 - [c202]Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting:
Probabilistic circuits that know what they don't know. UAI 2023: 2157-2167 - [c201]Sophie F. Jentzsch, Kristian Kersting:
ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models. WASSA@ACL 2023: 325-340 - 2022
- [c200]Mei Ling Fang, Devendra Singh Dhami, Kristian Kersting:
DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs. AIME 2022: 178-188 - [c199]Wolfgang Stammer, Marius Memmel, Patrick Schramowski, Kristian Kersting:
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. CVPR 2022: 10307-10318 - [c198]Nandini Ramanan, Phillip Odom, Erik Blasch, Kristian Kersting, Sriraam Natarajan:
Relational Active Feature Elicitation for DDDAS. DDDAS 2022: 227-232 - [c197]Lukas Struppek, Dominik Hintersdorf, Daniel Neider, Kristian Kersting:
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash. FAccT 2022: 58-69 - [c196]Patrick Schramowski, Christopher Tauchmann, Kristian Kersting:
Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content? FAccT 2022: 1350-1361 - [c195]Felix Friedrich, Patrick Schramowski, Christopher Tauchmann, Kristian Kersting:
Interactively Providing Explanations for Transformer Language Models. HHAI 2022: 285-287 - [c194]Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting:
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability. ICLR 2022 - [c193]Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correia, Antonia Adler, Kristian Kersting:
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. ICML 2022: 20522-20545 - [c192]Mina Ameli, Viktor Pfanschilling, Anar Amirli, Wolfgang Maaß, Kristian Kersting:
Unsupervised Multi-sensor Anomaly Localization with Explainable AI. AIAI (1) 2022: 507-519 - [c191]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
To Trust or Not To Trust Prediction Scores for Membership Inference Attacks. IJCAI 2022: 3043-3049 - [c190]Xuan Xie, Kristian Kersting, Daniel Neider:
Neuro-Symbolic Verification of Deep Neural Networks. IJCAI 2022: 3622-3628 - [c189]Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. KR 2022 - [c188]Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Neural-Probabilistic Answer Set Programming. KR 2022 - [c187]Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting, Iryna Gurevych:
Adaptable Adapters. NAACL-HLT 2022: 3742-3753 - [c186]Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M. Haas, Kristian Kersting, Sriraam Natarajan:
Explaining Deep Tractable Probabilistic Models: The sum-product network case. PGM 2022: 325-336 - [c185]Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting:
Predictive Whittle networks for time series. UAI 2022: 2320-2330 - 2021
- [c184]Xiaoting Shao, Arseny Skryagin, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions. AAAI 2021: 9533-9540 - [c183]Johannes Czech, Patrick Korus, Kristian Kersting:
Improving AlphaZero Using Monte-Carlo Graph Search. ICAPS 2021: 103-111 - [c182]Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations. CVPR 2021: 3619-3629 - [c181]Zhongjie Yu, Fabrizio Ventola, Kristian Kersting:
Whittle Networks: A Deep Likelihood Model for Time Series. ICML 2021: 12177-12186 - [c180]David Solans, Christopher Tauchmann, Aideen Farrell, Karolin Kappler, Hans-Hendrik Huber, Carlos Castillo, Kristian Kersting:
Learning to Classify Morals and Conventions: Artificial Intelligence in Terms of the Economics of Convention. ICWSM 2021: 691-702 - [c179]Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting:
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP 2021: 251-265 - [c178]Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting:
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. NeurIPS 2021: 15019-15031 - [c177]Steven Lang, Martin Mundt, Fabrizio Ventola, Robert Peharz, Kristian Kersting:
Elevating Perceptual Sample Quality in PCs through Differentiable Sampling. Pre-Registration Workshop @ NeurIPS 2021: 1-25 - [c176]Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting:
Leveraging probabilistic circuits for nonparametric multi-output regression. UAI 2021: 2008-2018 - 2020
- [c175]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Expanding PPML beyond Neural Networks. PPMLP@CCS 2020: 9-14 - [c174]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Privacy-Preserving Sum-Product Network Inference. ECAI 2020: 1946-1953 - [c173]Ute Schmid, Volker Tresp, Matthias Bethge, Kristian Kersting, Rainer Stiefelhagen:
Künstliche Intelligenz - Die dritte Welle. GI-Jahrestagung 2020: 91-95 - [c172]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. ICLR 2020 - [c171]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020 - [c170]Cigdem Turan, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Alfie: An Interactive Robot with Moral Compass. ICMI 2020: 758-759 - [c169]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML 2020: 7563-7574 - [c168]Matej Petkovic, Michelangelo Ceci, Kristian Kersting, Saso Dzeroski:
Estimating the Importance of Relational Features by Using Gradient Boosting. ISMIS 2020: 362-371 - [c167]Tjitze Rienstra, Matthias Thimm, Kristian Kersting, Xiaoting Shao:
Independence and D-separation in Abstract Argumentation. KR 2020: 713-722 - [c166]Kristian Kersting:
On Hybrid and Systems AI. LWDA 2020: 3 - [c165]Nandini Ramanan, Mayukh Das, Kristian Kersting, Sriraam Natarajan:
Discriminative Non-Parametric Learning of Arithmetic Circuits. PGM 2020: 353-364 - [c164]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM 2020: 401-412 - [c163]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Residual Sum-Product Networks. PGM 2020: 545-556 - [c162]Xiaoting Shao, Zhongjie Yu, Arseny Skryagin, Tjitze Rienstra, Matthias Thimm, Kristian Kersting:
Modelling Multivariate Ranking Functions with Min-Sum Networks. SUM 2020: 281-288 - 2019
- [c161]Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. AAAI 2019: 5207-5215 - [c160]Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan:
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. AAAI 2019: 7816-7824 - [c159]Sophie F. Jentzsch, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices. AIES 2019: 37-44 - [c158]Stefano Teso, Kristian Kersting:
Explanatory Interactive Machine Learning. AIES 2019: 239-245 - [c157]Lukas Weber, Lukas Sommer, Julian Oppermann, Alejandro Molina, Kristian Kersting, Andreas Koch:
Resource-Efficient Logarithmic Number Scale Arithmetic for SPN Inference on FPGAs. FPT 2019: 251-254 - [c156]Karl Stelzner, Robert Peharz, Kristian Kersting:
Faster Attend-Infer-Repeat with Tractable Probabilistic Models. ICML 2019: 5966-5975 - [c155]Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan:
Neural Networks for Relational Data. ILP 2019: 62-71 - [c154]Stefan Lüdtke, Alejandro Molina, Kristian Kersting, Thomas Kirste:
Gaussian Lifted Marginal Filtering. KI 2019: 230-243 - [c153]Claas Völcker, Alejandro Molina, Johannes Neumann, Dirk Westermann, Kristian Kersting:
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets. PKDD/ECML Workshops (1) 2019: 28-43 - [c152]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani:
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI 2019: 334-344 - 2018
- [c151]Alejandro Molina, Alexander Munteanu, Kristian Kersting:
Core Dependency Networks. AAAI 2018: 3820-3827 - [c150]Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting:
Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI 2018: 3828-3835 - [c149]Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina, Kristian Kersting, Floriana Esposito:
Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI 2018: 4163-4170 - [c148]Lukas Sommer, Julian Oppermann, Alejandro Molina, Carsten Binnig, Kristian Kersting, Andreas Koch:
Automatic Mapping of the Sum-Product Network Inference Problem to FPGA-Based Accelerators. ICCD 2018: 350-357 - [c147]Rudolf Lioutikov, Guilherme Maeda, Filipe Veiga, Kristian Kersting, Jan Peters:
Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives. ICRA 2018: 1-8 - [c146]Samuel Kolb, Martin Mladenov, Scott Sanner, Vaishak Belle, Kristian Kersting:
Efficient Symbolic Integration for Probabilistic Inference. IJCAI 2018: 5031-5037 - [c145]Stefan Lüdtke, Max Schröder, Sebastian Bader, Kristian Kersting, Thomas Kirste:
Lifted Filtering via Exchangeable Decomposition. IJCAI 2018: 5067-5073 - [c144]Parisa Kordjamshidi, Dan Roth, Kristian Kersting:
Systems AI: A Declarative Learning Based Programming Perspective. IJCAI 2018: 5464-5471 - [c143]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR 2018: 661-662 - 2017
- [c142]Martin Mladenov, Vaishak Belle, Kristian Kersting:
The Symbolic Interior Point Method. AAAI 2017: 1199-1205 - [c141]Martin Mladenov, Leonard Kleinhans, Kristian Kersting:
Lifted Inference for Convex Quadratic Programs. AAAI 2017: 2350-2356 - [c140]Alejandro Molina, Sriraam Natarajan, Kristian Kersting:
Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions. AAAI 2017: 2357-2363 - [c139]Shuo Yang, Fabian Hadiji, Kristian Kersting, Shaun J. Grannis, Sriraam Natarajan:
Modeling heart procedures from EHRs: An application of exponential families. BIBM 2017: 491-497 - [c138]Iryna Gurevych, Christian M. Meyer, Carsten Binnig, Johannes Fürnkranz, Kristian Kersting, Stefan Roth, Edwin Simpson:
Interactive Data Analytics for the Humanities. CICLing (1) 2017: 527-549 - [c137]Christopher Morris, Kristian Kersting, Petra Mutzel:
Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs. ICDM 2017: 327-336 - [c136]Zhao Xu, Kristian Kersting, Lorenzo von Ritter:
Stochastic Online Anomaly Analysis for Streaming Time Series. IJCAI 2017: 3189-3195 - [c135]Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, Sriraam Natarajan:
Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach. ILP 2017: 94-111 - [c134]Zhao Xu, Romain Vial, Kristian Kersting:
Graph Enhanced Memory Networks for Sentiment Analysis. ECML/PKDD (1) 2017: 374-389 - 2016
- [c133]Martin Mladenov, Danny Heinrich, Leonard Kleinhans, Felix Gonsior, Kristian Kersting:
RELOOP: A Python-Embedded Declarative Language for Relational Optimization. AAAI Workshop: Declarative Learning Based Programming 2016 - [c132]Shuo Yang, Tushar Khot, Kristian Kersting, Sriraam Natarajan:
Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. AAAI 2016: 2265-2271 - [c131]Sriraam Natarajan, Ameet Soni, Anurag Wazalwar, Dileep Viswanathan, Kristian Kersting:
Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction. Solving Large Scale Learning Tasks 2016: 331-345 - [c130]Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel:
Faster Kernels for Graphs with Continuous Attributes via Hashing. ICDM 2016: 1095-1100 - [c129]Joseph G. Taylor, Viktoriia Sharmanska, Kristian Kersting, David Weir, Novi Quadrianto:
Learning Using Unselected Features (LUFe). IJCAI 2016: 2060-2066 - [c128]Phillip Odom, Raksha Kumaraswamy, Kristian Kersting, Sriraam Natarajan:
Learning Through Advice-Seeking via Transfer. ILP 2016: 40-51 - [c127]Mayukh Das, Yuqing Wu, Tushar Khot, Kristian Kersting, Sriraam Natarajan:
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases. SDM 2016: 738-746 - 2015
- [c126]Rafet Sifa, Fabian Hadiji, Julian Runge, Anders Drachen, Kristian Kersting, Christian Bauckhage:
Predicting Purchase Decisions in Mobile Free-to-Play Games. AIIDE 2015: 79-85 - [c125]Shuo Yang, Kristian Kersting, Greg Terry, Jefferey Carr, Sriraam Natarajan:
Modeling Coronary Artery Calcification Levels from Behavioral Data in a Clinical Study. AIME 2015: 182-187 - [c124]Raksha Kumaraswamy, Phillip Odom, Kristian Kersting, David Leake, Sriraam Natarajan:
Transfer Learning via Relational Type Matching. ICDM 2015: 811-816 - [c123]Christian Bauckhage, Fabian Hadiji, Kristian Kersting:
How Viral Are Viral Videos? ICWSM 2015: 22-30 - [c122]Fabian Hadiji, Martin Mladenov, Christian Bauckhage, Kristian Kersting:
Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation. IJCAI 2015: 171-177 - [c121]Christian Bauckhage, Kristian Kersting, Fabian Hadiji:
Parameterizing the Distance Distribution of Undirected Networks. UAI 2015: 121-130 - [c120]Martin Mladenov, Kristian Kersting:
Equitable Partitions of Concave Free Energies. UAI 2015: 602-611 - [c119]Christoph Ide, Fabian Hadiji, Lars Habel, Alejandro Molina, Thomas Zaksek, Michael Schreckenberg, Kristian Kersting, Christian Wietfeld:
LTE Connectivity and Vehicular Traffic Prediction Based on Machine Learning Approaches. VTC Fall 2015: 1-5 - 2014
- [c118]Udi Apsel, Kristian Kersting, Martin Mladenov:
Lifting Relational MAP-LPs Using Cluster Signatures. AAAI 2014: 2403-2409 - [c117]Udi Apsel, Kristian Kersting, Martin Mladenov:
Lifting Relational MAP-LPs using Cluster Signatures. StarAI@AAAI 2014 - [c116]Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, David Poole:
Preface. StarAI@AAAI 2014 - [c115]Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole:
Relational Logistic Regression: The Directed Analog of Markov Logic Networks. StarAI@AAAI 2014 - [c114]Kristian Kersting, Martin Mladenov, Roman Garnett, Martin Grohe:
Power Iterated Color Refinement. AAAI 2014: 1904-1910 - [c113]Shrutika Poyrekar, Sriraam Natarajan, Kristian Kersting:
A Deeper Empirical Analysis of CBP Algorithm: Grounding Is the Bottleneck. StarAI@AAAI 2014 - [c112]Martin Mladenov, Kristian Kersting, Amir Globerson:
Efficient Lifting of MAP LP Relaxations Using k-Locality. AISTATS 2014: 623-632 - [c111]Fabian Hadiji, Rafet Sifa, Anders Drachen, Christian Thurau, Kristian Kersting, Christian Bauckhage:
Predicting player churn in the wild. CIG 2014: 1-8 - [c110]Martin Grohe, Kristian Kersting, Martin Mladenov, Erkal Selman:
Dimension Reduction via Colour Refinement. ESA 2014: 505-516 - [c109]Nils M. Kriege, Marion Neumann, Kristian Kersting, Petra Mutzel:
Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels. ICDM 2014: 881-886 - [c108]Shuo Yang, Tushar Khot, Kristian Kersting, Gautam Kunapuli, Kris Hauser, Sriraam Natarajan:
Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. ICDM 2014: 1085-1090 - [c107]Marion Neumann, Lisa Hallau, Benjamin Klatt, Kristian Kersting, Christian Bauckhage:
Erosion Band Features for Cell Phone Image Based Plant Disease Classification. ICPR 2014: 3315-3320 - [c106]Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik:
Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. ILP 2014: 92-107 - [c105]Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole:
Relational Logistic Regression. KR 2014 - [c104]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS 2014: 837-845 - [c103]David Poole, David Buchman, Seyed Mehran Kazemi, Kristian Kersting, Sriraam Natarajan:
Population Size Extrapolation in Relational Probabilistic Modelling. SUM 2014: 292-305 - [c102]Martin Mladenov, Amir Globerson, Kristian Kersting:
Lifted Message Passing as Reparametrization of Graphical Models. UAI 2014: 603-612 - [c101]Christian Bauckhage, Kristian Kersting, Bashir Rastegarpanah:
Collective attention to social media evolves according to diffusion models. WWW (Companion Volume) 2014: 223-224 - 2013
- [c100]Babak Ahmadi, Kristian Kersting, Sriraam Natarajan:
MapReduce Lifting for Belief Propagation. StarAI@AAAI 2013 - [c99]Vibhav Gogate, Kristian Kersting, Sriraam Natarajan, David Poole:
Preface. StarAI@AAAI 2013 - [c98]Fabian Hadiji, Kristian Kersting:
Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP. AAAI 2013: 394-400 - [c97]Fabian Hadiji, Kristian Kersting:
Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP. StarAI@AAAI 2013 - [c96]Martin Mladenov, Kristian Kersting:
Lifted Inference via k-Locality. StarAI@AAAI 2013 - [c95]Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik:
Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. StarAI@AAAI 2013 - [c94]Marion Neumann, Roman Garnett, Kristian Kersting:
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels. ACML 2013: 357-372 - [c93]Sriraam Natarajan, Kristian Kersting, Edward Hak-Sing Ip, David R. Jacobs Jr., Jeffrey Carr:
Early Prediction of Coronary Artery Calcification Levels Using Machine Learning. IAAI 2013: 1557-1562 - [c92]Christian Bauckhage, Kristian Kersting, Fabian Hadiji:
Mathematical Models of Fads Explain the Temporal Dynamics of Internet Memes. ICWSM 2013 - [c91]Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli:
Accelerating Imitation Learning in Relational Domains via Transfer by Initialization. ILP 2013: 64-75 - 2012
- [c90]Kristian Kersting, Zhao Xu, Mirwaes Wahabzada, Christian Bauckhage, Christian Thurau, Christoph Römer, Agim Ballvora, Uwe Rascher, Jens Leon, Lutz Plümer:
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images. AAAI 2012: 302-308 - [c89]Christian Bauckhage, Kristian Kersting, Rafet Sifa, Christian Thurau, Anders Drachen, Alessandro Canossa:
How players lose interest in playing a game: An empirical study based on distributions of total playing times. CIG 2012: 139-146 - [c88]Kristian Kersting:
Lifted Probabilistic Inference. ECAI 2012: 33-38 - [c87]Zhao Xu, Kristian Kersting, Christian Bauckhage:
Efficient Learning for Hashing Proportional Data. ICDM 2012: 735-744 - [c86]Sriraam Natarajan, Saket Joshi, Baidya Nath Saha, Adam Edwards, Tushar Khot, Elizabeth Moody, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian:
A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain. ICMLA (1) 2012: 203-208 - [c85]Daan Fierens, Kristian Kersting, Jesse Davis, Jian Chen, Martin Mladenov:
Pairwise Markov Logic. ILP 2012: 58-73 - [c84]Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting:
Symbolic Dynamic Programming for Continuous State and Observation POMDPs. NIPS 2012: 1403-1411 - [c83]Marion Neumann, Novi Patricia, Roman Garnett, Kristian Kersting:
Efficient Graph Kernels by Randomization. ECML/PKDD (1) 2012: 378-393 - [c82]Babak Ahmadi, Kristian Kersting, Sriraam Natarajan:
Lifted Online Training of Relational Models with Stochastic Gradient Methods. ECML/PKDD (1) 2012: 585-600 - [c81]Kristian Kersting, Christian Bauckhage, Christian Thurau, Mirwaes Wahabzada:
Matrix Factorization as Search. ECML/PKDD (2) 2012: 850-853 - [c80]Kristian Kersting, Mirwaes Wahabzada, Christoph Römer, Christian Thurau, Agim Ballvora, Uwe Rascher, Jens Leon, Christian Bauckhage, Lutz Plümer:
Simplex Distributions for Embedding Data Matrices over Time. SDM 2012: 295-306 - [c79]Christian Thurau, Kristian Kersting, Christian Bauckhage:
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study. SDM 2012: 684-695 - [c78]Daan Fierens, Kristian Kersting:
From Lifted Inference to Lifted Models. StarAI@UAI 2012 - [c77]Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli:
Accelarating Imitation Learning in Relational Domains via Transfer by Initialization. StarAI@UAI 2012 - [c76]David Poole, David Buchman, Sriraam Natarajan, Kristian Kersting:
Aggregation and Population Growth: The Relational Logistic Regression and Markov Logic Cases. StarAI@UAI 2012 - [c75]Mirwaes Wahabzada, Kristian Kersting, Christian Bauckhage, Christoph Römer, Agim Ballvora, Francisco Pinto, Uwe Rascher, Jens Leon, Lutz Ploemer:
Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants. UAI 2012: 852-862 - [c74]Martin Mladenov, Babak Ahmadi, Kristian Kersting:
Lifted Linear Programming. AISTATS 2012: 788-797 - [c73]Martin Schiegg, Marion Neumann, Kristian Kersting:
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data. AISTATS 2012: 1002-1011 - 2011
- [c72]Marion Neumann, Babak Ahmadi, Kristian Kersting:
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation. AAAI 2011: 447-452 - [c71]Mirwaes Wahabzada, Kristian Kersting, Anja Pilz, Christian Bauckhage:
More influence means less work: fast latent dirichlet allocation by influence scheduling. CIKM 2011: 2273-2276 - [c70]Kristian Kersting:
Invited Talk: Increasing Representational Power and Scaling Inference in Reinforcement Learning. EWRL 2011: 2 - [c69]Ahmed Jawad, Kristian Kersting, Natalia V. Andrienko:
Where traffic meets DNA: mobility mining using biological sequence analysis revisited. GIS 2011: 357-360 - [c68]Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik:
Learning Markov Logic Networks via Functional Gradient Boosting. ICDM 2011: 320-329 - [c67]Zhao Xu, Kristian Kersting:
Multi-task Learning with Task Relations. ICDM 2011: 884-893 - [c66]Babak Ahmadi, Kristian Kersting, Scott Sanner:
Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter. IJCAI 2011: 1152-1158 - [c65]Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. IJCAI 2011: 1414-1420 - [c64]Fabian Hadiji, Babak Ahmadi, Kristian Kersting:
Efficient Sequential Clamping for Lifted Message Passing. KI 2011: 122-133 - [c63]Babak Ahmadi, Martin Mladenov, Kristian Kersting, Scott Sanner:
On Lifted PageRank, Kalman Filter and Towards Lifted Linear Program Solving. LWA 2011: 35-42 - [c62]Ahmed Jawad, Kristian Kersting, Natalia V. Andrienko:
Biological Sequence Analysis meets Mobility Mining. LWA 2011: 73-80 - [c61]Babak Ahmadi, Salah Zayakh, Fabian Hadiji, Kristian Kersting:
O Scientist, Where Art Thou? Affiliation Propagation for Geo-Referencing Scientific Publications. LWA 2011: 133-136 - [c60]Mirwaes Wahabzada, Kristian Kersting:
Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation. ECML/PKDD (3) 2011: 475-490 - 2010
- [c59]Fabian Hadiji, Kristian Kersting, Babak Ahmadi:
Lifted Message Passing for Satisfiability. StarAI@AAAI 2010 - [c58]Kristian Kersting, Youssef El Massaoudi, Fabian Hadiji, Babak Ahmadi:
Informed Lifting for Message-Passing. AAAI 2010: 1181-1186 - [c57]Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. StarAI@AAAI 2010 - [c56]Scott Sanner, Kristian Kersting:
Symbolic Dynamic Programming for First-order POMDPs. AAAI 2010: 1140-1146 - [c55]Saket Joshi, Kristian Kersting, Roni Khardon:
Self-Taught Decision Theoretic Planning with First Order Decision Diagrams. ICAPS 2010: 89-96 - [c54]Christian Thurau, Kristian Kersting, Christian Bauckhage:
Yes we can: simplex volume maximization for descriptive web-scale matrix factorization. CIKM 2010: 1785-1788 - [c53]Ahmed Jawad, Kristian Kersting:
Kernelized map matching. GIS 2010: 454-457 - [c52]Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
Multi-Agent Inverse Reinforcement Learning. ICMLA 2010: 395-400 - [c51]Jens Behley, Kristian Kersting, Dirk Schulz, Volker Steinhage, Armin B. Cremers:
Learning to hash logistic regression for fast 3D scan point classification. IROS 2010: 5960-5965 - [c50]Babak Ahmadi, Kristian Kersting, Fabian Hadiji:
Lifted Conditioning for Pairwise Marginals and Beyond. LWA 2010: 13-18 - [c49]Ahmed Jawad, Kristian Kersting:
Kernelized Map Matching for noisy trajectories. LWA 2010: 89-96 - [c48]Kristian Kersting, Mirwaes Wahabzada, Christian Thurau, Christian Bauckhage:
Convex NMF on Non-Convex Massiv Data. LWA 2010: 97-104 - [c47]Novi Quadrianto, Kristian Kersting, Tinne Tuytelaars, Wray L. Buntine:
Beyond 2D-grids: a dependence maximization view on image browsing. Multimedia Information Retrieval 2010: 339-348 - [c46]Tobias Lang, Marc Toussaint, Kristian Kersting:
Exploration in Relational Worlds. ECML/PKDD (2) 2010: 178-194 - [c45]Mirwaes Wahabzada, Zhao Xu, Kristian Kersting:
Topic Models Conditioned on Relations. ECML/PKDD (3) 2010: 402-417 - [c44]Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) 2010: 434-450 - [c43]Zhao Xu, Kristian Kersting, Thorsten Joachims:
Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes. ECML/PKDD (3) 2010: 499-514 - [c42]Kristian Kersting, Mirwaes Wahabzada, Christian Thurau, Christian Bauckhage:
Hierarchical Convex NMF for Clustering Massive Data. ACML 2010: 253-268 - 2009
- [c41]Marion Neumann, Kristian Kersting, Zhao Xu, Daniel Schulz:
Stacked Gaussian Process Learning. ICDM 2009: 387-396 - [c40]Christian Thurau, Kristian Kersting, Christian Bauckhage:
Convex Non-negative Matrix Factorization in the Wild. ICDM 2009: 523-532 - [c39]Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tibério S. Caetano, Wray L. Buntine:
Kernel Conditional Quantile Estimation via Reduction Revisited. ICDM 2009: 938-943 - [c38]Zhao Xu, Kristian Kersting, Volker Tresp:
Multi-Relational Learning with Gaussian Processes. IJCAI 2009: 1309-1314 - [c37]Saket Joshi, Kristian Kersting, Roni Khardon:
Generalized First Order Decision Diagrams for First Order Markov Decision Processes. IJCAI 2009: 1916-1921 - [c36]Hannes Schulz, Kristian Kersting, Andreas Karwath:
ILP, the Blind, and the Elephant: Euclidean Embedding of Co-proven Queries. ILP 2009: 209-216 - [c35]Kristian Kersting, Zhao Xu:
Learning Preferences with Hidden Common Cause Relations. ECML/PKDD (1) 2009: 676-691 - [c34]Kristian Kersting, Babak Ahmadi, Sriraam Natarajan:
Counting Belief Propagation. UAI 2009: 277-284 - 2008
- [c33]Brian Milch, Luke S. Zettlemoyer, Kristian Kersting, Michael Haimes, Leslie Pack Kaelbling:
Lifted Probabilistic Inference with Counting Formulas. AAAI 2008: 1062-1068 - [c32]Andreas Karwath, Kristian Kersting, Niels Landwehr:
Boosting Relational Sequence Alignments. ICDM 2008: 857-862 - [c31]Kristian Kersting, Kurt Driessens:
Non-parametric policy gradients: a unified treatment of propositional and relational domains. ICML 2008: 456-463 - [c30]Kristian Kersting:
SRL without Tears: An ILP Perspective. ILP 2008: 2 - [c29]Sriraam Natarajan, Hung Hai Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong:
Logical Hierarchical Hidden Markov Models for Modeling User Activities. ILP 2008: 192-209 - [c28]Christian Plagemann, Sebastian Mischke, Sam Prentice, Kristian Kersting, Nicholas Roy, Wolfram Burgard:
Learning predictive terrain models for legged robot locomotion. IROS 2008: 3545-3552 - [c27]Zhao Xu, Volker Tresp, Achim Rettinger, Kristian Kersting:
Social Network Mining with Nonparametric Relational Models. SNAKDD 2008: 77-96 - [c26]Olana Missura, Kristian Kersting, Thomas Gärtner:
Towards Engaging Games. LWA 2008: 77-83 - [c25]Christian Plagemann, Kristian Kersting, Wolfram Burgard:
Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness. ECML/PKDD (2) 2008: 204-219 - [c24]Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt:
Parameter Learning in Probabilistic Databases: A Least Squares Approach. ECML/PKDD (1) 2008: 473-488 - 2007
- [c23]Kristian Kersting, Christian Plagemann, Patrick Pfaff, Wolfram Burgard:
Most likely heteroscedastic Gaussian process regression. ICML 2007: 393-400 - [c22]Christian Plagemann, Kristian Kersting, Patrick Pfaff, Wolfram Burgard:
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders. Robotics: Science and Systems 2007 - 2006
- [c21]Uwe Dick, Kristian Kersting:
Fisher Kernels for Relational Data. ECML 2006: 114-125 - [c20]Bernd Gutmann, Kristian Kersting:
TildeCRF: Conditional Random Fields for Logical Sequences. ECML 2006: 174-185 - [c19]Rudolph Triebel, Kristian Kersting, Wolfram Burgard:
Robust 3D Scan Point Classification using Associative Markov Networks. ICRA 2006: 2603-2608 - [c18]Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen:
Revising Probabilistic Prolog Programs. ILP 2006: 30-33 - [c17]Andreas Karwath, Kristian Kersting:
Relational Sequence Alignments and Logos. ILP 2006: 290-304 - [c16]Alexandru Cocora, Kristian Kersting, Christian Plagemann, Wolfram Burgard, Luc De Raedt:
Learning Relational Navigation Policies. IROS 2006: 2792-2797 - 2005
- [c15]Luc De Raedt, Kristian Kersting, Sunna Torge:
Towards Learning Stochastic Logic Programs from Proof-Banks. AAAI 2005: 752-757 - [c14]Niels Landwehr, Kristian Kersting, Luc De Raedt:
nFOIL: Integrating Naïve Bayes and FOIL. AAAI 2005: 795-800 - [c13]Kristian Kersting, Tapani Raiko:
"Say EM" for Selecting Probabilistic Models for Logical Sequences. UAI 2005: 300-307 - 2004
- [c12]Luc De Raedt, Kristian Kersting:
Probabilistic Inductive Logic Programming. ALT 2004: 19-36 - [c11]Kristian Kersting, Thomas Gärtner:
Fisher Kernels for Logical Sequences. ECML 2004: 205-216 - [c10]Kristian Kersting, Martijn van Otterlo, Luc De Raedt:
Bellman goes relational. ICML 2004 - [c9]Kristian Kersting, Luc De Raedt:
Logical Markov Decision Programs and the Convergence of Logical TD(lambda). ILP 2004: 180-197 - [c8]Kristian Kersting, Uwe Dick:
Balios - The Engine for Bayesian Logic Programs. PKDD 2004: 549-551 - 2003
- [c7]Jörg Fischer, Kristian Kersting:
Scaled CGEM: A Fast Accelerated EM. ECML 2003: 133-144 - [c6]Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt:
Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models. Pacific Symposium on Biocomputing 2003: 192-203 - 2002
- [c5]Kristian Kersting, Niels Landwehr:
Scaled Conjugate Gradients for Maximum Likelihood: An Empirical Comparison with the EM Algorithm. Probabilistic Graphical Models 2002 - [c4]Kristian Kersting, Tapani Raiko, Luc De Raedt:
Logical Hidden Markov Models (Extendes abstract). Probabilistic Graphical Models 2002 - 2001
- [c3]Kristian Kersting, Luc De Raedt:
Adaptive Bayesian Logic Programs. ILP 2001: 104-117 - [c2]Kristian Kersting, Luc De Raedt:
Towards Combining Inductive Logic Programming with Bayesian Networks. ILP 2001: 118-131 - 2000
- [c1]Kristian Kersting, Luc De Raedt:
Bayesian Logic Programs. ILP Work-in-progress reports 2000
Parts in Books or Collections
- 2016
- [p5]Kristian Kersting, Christian Bauckhage, Mirwaes Wahabzada, Anne-Katrin Mahlein, Ulrike Steiner, Erich-Christian Oerke, Christoph Römer, Lutz Plümer:
Feeding the World with Big Data: Uncovering Spectral Characteristics and Dynamics of Stressed Plants. Computational Sustainability 2016: 99-120 - 2010
- [p4]Luc De Raedt, Angelika Kimmig, Bernd Gutmann, Kristian Kersting, Vítor Santos Costa, Hannu Toivonen:
Probabilistic Inductive Querying Using ProbLog. Inductive Databases and Constraint-Based Data Mining 2010: 229-262 - 2008
- [p3]Luc De Raedt, Kristian Kersting:
Probabilistic Inductive Logic Programming. Probabilistic Inductive Logic Programming 2008: 1-27 - [p2]Kristian Kersting, Luc De Raedt, Bernd Gutmann, Andreas Karwath, Niels Landwehr:
Relational Sequence Learning. Probabilistic Inductive Logic Programming 2008: 28-55 - [p1]Kristian Kersting, Luc De Raedt:
Basic Principles of Learning Bayesian Logic Programs. Probabilistic Inductive Logic Programming 2008: 189-221
Editorship
- 2021
- [e13]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12457, Springer 2021, ISBN 978-3-030-67657-5 [contents] - [e12]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12458, Springer 2021, ISBN 978-3-030-67660-5 [contents] - [e11]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part III. Lecture Notes in Computer Science 12459, Springer 2021, ISBN 978-3-030-67663-6 [contents] - 2017
- [e10]Gal Elidan, Kristian Kersting, Alexander Ihler:
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, UAI 2017, Sydney, Australia, August 11-15, 2017. AUAI Press 2017 [contents] - 2016
- [e9]Jörg Lässig, Kristian Kersting, Katharina Morik:
Computational Sustainability. Studies in Computational Intelligence 645, Springer 2016, ISBN 978-3-319-31856-1 [contents] - 2013
- [e8]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I. Lecture Notes in Computer Science 8188, Springer 2013, ISBN 978-3-642-40987-5 [contents] - [e7]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II. Lecture Notes in Computer Science 8189, Springer 2013, ISBN 978-3-642-40990-5 [contents] - [e6]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III. Lecture Notes in Computer Science 8190, Springer 2013, ISBN 978-3-642-40993-6 [contents] - 2012
- [e5]Kristian Kersting, Marc Toussaint:
STAIRS 2012 - Proceedings of the Sixth Starting AI Researchers' Symposium, Montpellier, France, 27-28 August 2012. Frontiers in Artificial Intelligence and Applications 241, IOS Press 2012, ISBN 978-1-61499-095-6 [contents] - 2010
- [e4]Henry A. Kautz, Kristian Kersting, Sriraam Natarajan, David Poole:
2nd International Workshop on Statistical Relational AI (StaRAI-12), held at the Uncertainty in Artificial Intelligence Conference (UAI 2012), Catalina Island, CA, USA, August 18, 2012. 2010 [contents] - 2008
- [e3]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen H. Muggleton:
Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007. Dagstuhl Seminar Proceedings 07161, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008 [contents] - [e2]Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen H. Muggleton:
Probabilistic Inductive Logic Programming - Theory and Applications. Lecture Notes in Computer Science 4911, Springer 2008, ISBN 978-3-540-78651-1 [contents] - 2007
- [e1]Paolo Frasconi, Kristian Kersting, Koji Tsuda:
Mining and Learning with Graphs, MLG 2007, Firence, Italy, August 1-3, 2007, Proceedings. 2007 [contents]
Reference Works
- 2017
- [r6]Novi Quadrianto, Kristian Kersting, Zhao Xu:
Gaussian Process. Encyclopedia of Machine Learning and Data Mining 2017: 535-548 - [r5]Luc De Raedt, Kristian Kersting:
Statistical Relational Learning. Encyclopedia of Machine Learning and Data Mining 2017: 1177-1187 - [r4]Scott Sanner, Kristian Kersting:
Symbolic Dynamic Programming. Encyclopedia of Machine Learning and Data Mining 2017: 1220-1228 - 2010
- [r3]Novi Quadrianto, Kristian Kersting, Zhao Xu:
Gaussian Process. Encyclopedia of Machine Learning 2010: 428-439 - [r2]Luc De Raedt, Kristian Kersting:
Statistical Relational Learning. Encyclopedia of Machine Learning 2010: 916-924 - [r1]Scott Sanner, Kristian Kersting:
Symbolic Dynamic Programming. Encyclopedia of Machine Learning 2010: 946-954
Informal and Other Publications
- 2024
- [i155]Quentin Delfosse, Sebastian Sztwiertnia, Wolfgang Stammer, Mark Rothermel, Kristian Kersting:
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents. CoRR abs/2401.05821 (2024) - [i154]Felix Friedrich, Katharina Hämmerl, Patrick Schramowski, Jindrich Libovický, Kristian Kersting, Alexander Fraser:
Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You. CoRR abs/2401.16092 (2024) - [i153]Felix Helfenstein, Jannis Blüml, Johannes Czech, Kristian Kersting:
Checkmating One, by Using Many: Combining Mixture of Experts with MCTS to Improve in Chess. CoRR abs/2401.16852 (2024) - [i152]Roshni Kamath, Rupert Mitchell, Subarnaduti Paul, Kristian Kersting, Martin Mundt:
BOWLL: A Deceptively Simple Open World Lifelong Learner. CoRR abs/2402.04814 (2024) - [i151]Florian Peter Busch, Roshni Kamath, Rupert Mitchell, Wolfgang Stammer, Kristian Kersting, Martin Mundt:
Where is the Truth? The Risk of Getting Confounded in a Continual World. CoRR abs/2402.06434 (2024) - [i150]Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting:
Pix2Code: Learning to Compose Neural Visual Concepts as Programs. CoRR abs/2402.08280 (2024) - [i149]Cedric Derstroff, Jannis Brugger, Jannis Blüml, Mira Mezini, Stefan Kramer, Kristian Kersting:
Amplifying Exploration in Monte-Carlo Tree Search by Focusing on the Unknown. CoRR abs/2402.08511 (2024) - [i148]Lukas Struppek, Minh Hieu Le, Dominik Hintersdorf, Kristian Kersting:
Exploring the Adversarial Capabilities of Large Language Models. CoRR abs/2402.09132 (2024) - [i147]Maurice Kraus, David Steinmann, Antonia Wüst, Andre Kokozinski, Kristian Kersting:
Right on Time: Revising Time Series Models by Constraining their Explanations. CoRR abs/2402.12921 (2024) - [i146]Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting:
DeiSAM: Segment Anything with Deictic Prompting. CoRR abs/2402.14123 (2024) - [i145]Maurice Kraus, Felix Divo, David Steinmann, Devendra Singh Dhami, Kristian Kersting:
United We Pretrain, Divided We Fail! Representation Learning for Time Series by Pretraining on 75 Datasets at Once. CoRR abs/2402.15404 (2024) - [i144]Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan:
Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits. CoRR abs/2403.03281 (2024) - [i143]Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli:
Mechanistic Design and Scaling of Hybrid Architectures. CoRR abs/2403.17844 (2024) - 2023
- [i142]Mayukh Deb, Björn Deiseroth, Samuel Weinbach, Patrick Schramowski, Kristian Kersting:
AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation. CoRR abs/2301.08110 (2023) - [i141]Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting:
SEGA: Instructing Diffusion using Semantic Dimensions. CoRR abs/2301.12247 (2023) - [i140]Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting:
Probabilistic Circuits That Know What They Don't Know. CoRR abs/2302.06544 (2023) - [i139]Felix Friedrich, Patrick Schramowski, Manuel Brack, Lukas Struppek, Dominik Hintersdorf, Sasha Luccioni, Kristian Kersting:
Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness. CoRR abs/2302.10893 (2023) - [i138]Lukas Struppek, Dominik Hintersdorf, Felix Friedrich, Manuel Brack, Patrick Schramowski, Kristian Kersting:
Image Classifiers Leak Sensitive Attributes About Their Classes. CoRR abs/2303.09289 (2023) - [i137]Felix Friedrich, David Steinmann, Kristian Kersting:
One Explanation Does Not Fit XIL. CoRR abs/2304.07136 (2023) - [i136]Johannes Czech, Jannis Blüml, Kristian Kersting:
Representation Matters: The Game of Chess Poses a Challenge to Vision Transformers. CoRR abs/2304.14918 (2023) - [i135]Jannis Weil, Johannes Czech, Tobias Meuser, Kristian Kersting:
Know your Enemy: Investigating Monte-Carlo Tree Search with Opponent Models in Pommerman. CoRR abs/2305.13206 (2023) - [i134]Marco Bellagente, Manuel Brack, Hannah Teufel, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert Baldock, Souradeep Nanda, Koen Oostermeijer, Andrés Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach:
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation. CoRR abs/2305.15296 (2023) - [i133]Manuel Brack, Felix Friedrich, Patrick Schramowski, Kristian Kersting:
Mitigating Inappropriateness in Image Generation: Can there be Value in Reflecting the World's Ugliness? CoRR abs/2305.18398 (2023) - [i132]Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. CoRR abs/2306.01439 (2023) - [i131]Steven Braun, Martin Mundt, Kristian Kersting:
Deep Classifier Mimicry without Data Access. CoRR abs/2306.02090 (2023) - [i130]Subarnaduti Paul, Lars-Joel Frey, Roshni Kamath, Kristian Kersting, Martin Mundt:
Masked Autoencoders are Efficient Continual Federated Learners. CoRR abs/2306.03542 (2023) - [i129]Sophie F. Jentzsch, Kristian Kersting:
ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models. CoRR abs/2306.04563 (2023) - [i128]Lukas Helff, Wolfgang Stammer, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
V-LoL: A Diagnostic Dataset for Visual Logical Learning. CoRR abs/2306.07743 (2023) - [i127]Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Scalable Neural-Probabilistic Answer Set Programming. CoRR abs/2306.08397 (2023) - [i126]Quentin Delfosse, Jannis Blüml, Bjarne Gregori, Sebastian Sztwiertnia, Kristian Kersting:
OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments. CoRR abs/2306.08649 (2023) - [i125]Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
Learning Differentiable Logic Programs for Abstract Visual Reasoning. CoRR abs/2307.00928 (2023) - [i124]Rupert Mitchell, Martin Mundt, Kristian Kersting:
Self Expanding Neural Networks. CoRR abs/2307.04526 (2023) - [i123]Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth:
Vision Relation Transformer for Unbiased Scene Graph Generation. CoRR abs/2308.09472 (2023) - [i122]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
Balancing Transparency and Risk: The Security and Privacy Risks of Open-Source Machine Learning Models. CoRR abs/2308.09490 (2023) - [i121]Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting:
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal. CoRR abs/2308.13067 (2023) - [i120]David Steinmann, Wolfgang Stammer, Felix Friedrich, Kristian Kersting:
Learning to Intervene on Concept Bottlenecks. CoRR abs/2308.13453 (2023) - [i119]Wolfgang Stammer, Felix Friedrich, David Steinmann, Hikaru Shindo, Kristian Kersting:
Learning by Self-Explaining. CoRR abs/2309.08395 (2023) - [i118]Manuel Brack, Patrick Schramowski, Kristian Kersting:
Distilling Adversarial Prompts from Safety Benchmarks: Report for the Adversarial Nibbler Challenge. CoRR abs/2309.11575 (2023) - [i117]Lukas Struppek, Martin B. Hentschel, Clifton Poth, Dominik Hintersdorf, Kristian Kersting:
Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data. CoRR abs/2310.06372 (2023) - [i116]Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks. CoRR abs/2310.06549 (2023) - [i115]Dominik Hintersdorf, Lukas Struppek, Daniel Neider, Kristian Kersting:
Defending Our Privacy With Backdoors. CoRR abs/2310.08320 (2023) - [i114]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Do Not Marginalize Mechanisms, Rather Consolidate! CoRR abs/2310.08377 (2023) - [i113]Benjamin Hilprecht, Kristian Kersting, Carsten Binnig:
SPARE: A Single-Pass Neural Model for Relational Databases. CoRR abs/2310.13581 (2023) - [i112]Björn Deiseroth, Max Meuer, Nikolas Gritsch, Constantin Eichenberg, Patrick Schramowski, Matthias Aßenmacher, Kristian Kersting:
Divergent Token Metrics: Measuring degradation to prune away LLM components - and optimize quantization. CoRR abs/2311.01544 (2023) - [i111]Yannik Keller, Jannis Blüml, Gopika Sudhakaran, Kristian Kersting:
From Images to Connections: Can DQN with GNNs learn the Strategic Game of Hex? CoRR abs/2311.13414 (2023) - [i110]Manuel Brack, Felix Friedrich, Katharina Kornmeier, Linoy Tsaban, Patrick Schramowski, Kristian Kersting, Apolinário Passos:
LEDITS++: Limitless Image Editing using Text-to-Image Models. CoRR abs/2311.16711 (2023) - [i109]Zhongjie Yu, Martin Trapp, Kristian Kersting:
Characteristic Circuits. CoRR abs/2312.07790 (2023) - 2022
- [i108]Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correia, Antonia Adler, Kristian Kersting:
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. CoRR abs/2201.12179 (2022) - [i107]Xiaoting Shao, Karl Stelzner, Kristian Kersting:
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. CoRR abs/2202.00391 (2022) - [i106]Patrick Schramowski, Christopher Tauchmann, Kristian Kersting:
Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content? CoRR abs/2202.06675 (2022) - [i105]Xuan Xie, Kristian Kersting, Daniel Neider:
Neuro-Symbolic Verification of Deep Neural Networks. CoRR abs/2203.00938 (2022) - [i104]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
A Typology to Explore and Guide Explanatory Interactive Machine Learning. CoRR abs/2203.03668 (2022) - [i103]Katharina Hämmerl, Björn Deiseroth, Patrick Schramowski, Jindrich Libovický, Alexander Fraser, Kristian Kersting:
Do Multilingual Language Models Capture Differing Moral Norms? CoRR abs/2203.09904 (2022) - [i102]Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting:
Finding Structure and Causality in Linear Programs. CoRR abs/2203.15274 (2022) - [i101]Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting, Iryna Gurevych:
Adaptable Adapters. CoRR abs/2205.01549 (2022) - [i100]Xiaoting Shao, Kristian Kersting:
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models. CoRR abs/2205.07774 (2022) - [i99]David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Machines Explaining Linear Programs. CoRR abs/2206.07194 (2022) - [i98]Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation. CoRR abs/2206.07195 (2022) - [i97]Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Towards a Solution to Bongard Problems: A Causal Approach. CoRR abs/2206.07196 (2022) - [i96]Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami:
Attributions Beyond Neural Networks: The Linear Program Case. CoRR abs/2206.07203 (2022) - [i95]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Can Foundation Models Talk Causality? CoRR abs/2206.10591 (2022) - [i94]Jonas Seng, Pooja Prasad, Devendra Singh Dhami, Kristian Kersting:
HANF: Hyperparameter And Neural Architecture Search in Federated Learning. CoRR abs/2206.12342 (2022) - [i93]Manuel Brack, Patrick Schramowski, Björn Deiseroth, Kristian Kersting:
ILLUME: Rationalizing Vision-Language Models by Interacting with their Jabber. CoRR abs/2208.08241 (2022) - [i92]Frieder Uhlig, Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
Transformer-Boosted Anomaly Detection with Fuzzy Hashes. CoRR abs/2208.11367 (2022) - [i91]Björn Deiseroth, Patrick Schramowski, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems. CoRR abs/2208.13518 (2022) - [i90]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models. CoRR abs/2209.07341 (2022) - [i89]Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
The Biased Artist: Exploiting Cultural Biases via Homoglyphs in Text-Guided Image Generation Models. CoRR abs/2209.08891 (2022) - [i88]Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Revision Transformers: Getting RiT of No-Nos. CoRR abs/2210.10332 (2022) - [i87]Lukas Struppek, Dominik Hintersdorf, Kristian Kersting:
Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models. CoRR abs/2211.02408 (2022) - [i86]Patrick Schramowski, Manuel Brack, Björn Deiseroth, Kristian Kersting:
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models. CoRR abs/2211.05105 (2022) - [i85]Katharina Hämmerl, Björn Deiseroth, Patrick Schramowski, Jindrich Libovický, Constantin A. Rothkopf, Alexander Fraser, Kristian Kersting:
Speaking Multiple Languages Affects the Moral Bias of Language Models. CoRR abs/2211.07733 (2022) - [i84]Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbacher, Dwarak Vittal, Kristian Kersting:
Boosting Object Representation Learning via Motion and Object Continuity. CoRR abs/2211.09771 (2022) - [i83]Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Differentiable Meta logical Programming. CoRR abs/2211.11650 (2022) - [i82]Manuel Brack, Patrick Schramowski, Felix Friedrich, Dominik Hintersdorf, Kristian Kersting:
The Stable Artist: Steering Semantics in Diffusion Latent Space. CoRR abs/2212.06013 (2022) - [i81]Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting:
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges. CoRR abs/2212.12570 (2022) - [i80]Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling:
Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161). Dagstuhl Reports 12(4): 13-25 (2022) - 2021
- [i79]Quentin Delfosse, Patrick Schramowski, Alejandro Molina, Kristian Kersting:
Recurrent Rational Networks. CoRR abs/2102.09407 (2021) - [i78]Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting:
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. CoRR abs/2102.10440 (2021) - [i77]Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf, Kristian Kersting:
Language Models have a Moral Dimension. CoRR abs/2103.11790 (2021) - [i76]Karl Stelzner, Kristian Kersting, Adam R. Kosiorek:
Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation. CoRR abs/2104.01148 (2021) - [i75]Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer, Tim Grube, Kristian Kersting, Max Mühlhäuser:
User Label Leakage from Gradients in Federated Learning. CoRR abs/2105.09369 (2021) - [i74]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Intriguing Parameters of Structural Causal Models. CoRR abs/2105.12697 (2021) - [i73]Nils Thoma, Zhongjie Yu, Fabrizio Ventola, Kristian Kersting:
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting. CoRR abs/2106.04148 (2021) - [i72]Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting:
Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression. CoRR abs/2106.08687 (2021) - [i71]Maximilian Otte, Quentin Delfosse, Johannes Czech, Kristian Kersting:
Generative Adversarial Neural Cellular Automata. CoRR abs/2108.04328 (2021) - [i70]Matej Zecevic, Devendra Singh Dhami, Petar Velickovic, Kristian Kersting:
Relating Graph Neural Networks to Structural Causal Models. CoRR abs/2109.04173 (2021) - [i69]Steven Lang, Fabrizio Ventola, Kristian Kersting:
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection. CoRR abs/2109.06148 (2021) - [i68]Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting:
Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits. CoRR abs/2109.06587 (2021) - [i67]Patrick Schramowski, Felix Friedrich, Christopher Tauchmann, Kristian Kersting:
Interactively Generating Explanations for Transformer Language Models. CoRR abs/2110.02058 (2021) - [i66]Matej Zecevic, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting:
Structural Causal Interpretation Theorem. CoRR abs/2110.02395 (2021) - [i65]Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting:
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability. CoRR abs/2110.03331 (2021) - [i64]Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming. CoRR abs/2110.03395 (2021) - [i63]Patrick Schramowski, Kristian Kersting:
Inferring Offensiveness In Images From Natural Language Supervision. CoRR abs/2110.04222 (2021) - [i62]Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Neuro-Symbolic Forward Reasoning. CoRR abs/2110.09383 (2021) - [i61]Athresh Karanam, Saurabh Mathur, Predrag Radivojac, Kristian Kersting, Sriraam Natarajan:
Explaining Deep Tractable Probabilistic Models: The sum-product network case. CoRR abs/2110.09778 (2021) - [i60]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
On the Tractability of Neural Causal Inference. CoRR abs/2110.12052 (2021) - [i59]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
The Causal Loss: Driving Correlation to Imply Causation. CoRR abs/2110.12066 (2021) - [i58]Lukas Struppek, Dominik Hintersdorf, Daniel Neider, Kristian Kersting:
Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash. CoRR abs/2111.06628 (2021) - [i57]Dominik Hintersdorf, Lukas Struppek, Kristian Kersting:
Do Not Trust Prediction Scores for Membership Inference Attacks. CoRR abs/2111.09076 (2021) - [i56]Wolfgang Stammer, Marius Memmel, Patrick Schramowski, Kristian Kersting:
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. CoRR abs/2112.02290 (2021) - 2020
- [i55]Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting:
Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations. CoRR abs/2001.05371 (2020) - [i54]Amos Treiber, Alejandro Molina, Christian Weinert, Thomas Schneider, Kristian Kersting:
CryptoSPN: Privacy-preserving Sum-Product Network Inference. CoRR abs/2002.00801 (2020) - [i53]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR abs/2004.06231 (2020) - [i52]Srijita Das, Sriraam Natarajan, Kaushik Roy, Ronald Parr, Kristian Kersting:
Fitted Q-Learning for Relational Domains. CoRR abs/2006.05595 (2020) - [i51]Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann:
TUDataset: A collection of benchmark datasets for learning with graphs. CoRR abs/2007.08663 (2020) - [i50]Cigdem Turan, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting:
Alfie: An Interactive Robot with a Moral Compass. CoRR abs/2009.05349 (2020) - [i49]Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations. CoRR abs/2011.12854 (2020) - [i48]Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer:
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation. CoRR abs/2012.08459 (2020) - [i47]Johannes Czech, Patrick Korus, Kristian Kersting:
Monte-Carlo Graph Search for AlphaZero. CoRR abs/2012.11045 (2020) - [i46]Kristian Kersting, Miryung Kim, Guy Van den Broeck, Thomas Zimmermann:
SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091). Dagstuhl Reports 10(2): 76-87 (2020) - 2019
- [i45]Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting:
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR abs/1901.03704 (2019) - [i44]Kristian Kersting, Jan Peters, Constantin A. Rothkopf:
Was ist eine Professur fuer Kuenstliche Intelligenz? CoRR abs/1903.09516 (2019) - [i43]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR abs/1905.08550 (2019) - [i42]Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni:
Neural-Symbolic Argumentation Mining: an Argument in Favour of Deep Learning and Reasoning. CoRR abs/1905.09103 (2019) - [i41]Parisa Kordjamshidi, Dan Roth, Kristian Kersting:
Declarative Learning-Based Programming as an Interface to AI Systems. CoRR abs/1906.07809 (2019) - [i40]Alejandro Molina, Patrick Schramowski, Kristian Kersting:
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks. CoRR abs/1907.06732 (2019) - [i39]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Random Sum-Product Forests with Residual Links. CoRR abs/1908.03250 (2019) - [i38]Johannes Czech, Moritz Willig, Alena Beyer, Kristian Kersting, Johannes Fürnkranz:
Learning to play the Chess Variant Crazyhouse above World Champion Level with Deep Neural Networks and Human Data. CoRR abs/1908.06660 (2019) - [i37]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig:
DeepDB: Learn from Data, not from Queries! CoRR abs/1909.00607 (2019) - [i36]Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan:
Neural Networks for Relational Data. CoRR abs/1909.04723 (2019) - [i35]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. CoRR abs/1910.02425 (2019) - [i34]Patrick Schramowski, Cigdem Turan, Sophie F. Jentzsch, Constantin A. Rothkopf, Kristian Kersting:
BERT has a Moral Compass: Improvements of ethical and moral values of machines. CoRR abs/1912.05238 (2019) - [i33]Michael Benedikt, Kristian Kersting, Phokion G. Kolaitis, Daniel Neider:
Logic and Learning (Dagstuhl Seminar 19361). Dagstuhl Reports 9(9): 1-22 (2019) - 2018
- [i32]Stefan Lüdtke, Max Schröder, Sebastian Bader, Kristian Kersting, Thomas Kirste:
Lifted Filtering via Exchangeable Decomposition. CoRR abs/1801.10495 (2018) - [i31]Patrick Schramowski, Christian Bauckhage, Kristian Kersting:
Neural Conditional Gradients. CoRR abs/1803.04300 (2018) - [i30]Stefano Teso, Kristian Kersting:
"Why Should I Trust Interactive Learners?" Explaining Interactive Queries of Classifiers to Users. CoRR abs/1805.08578 (2018) - [i29]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani:
Probabilistic Deep Learning using Random Sum-Product Networks. CoRR abs/1806.01910 (2018) - [i28]Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. CoRR abs/1807.09306 (2018) - [i27]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure Learning for Relational Logistic Regression: An Ensemble Approach. CoRR abs/1808.02123 (2018) - [i26]Moritz Kulessa, Alejandro Molina, Carsten Binnig, Benjamin Hilprecht, Kristian Kersting:
Model-based Approximate Query Processing. CoRR abs/1811.06224 (2018) - 2017
- [i25]Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel:
A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels. CoRR abs/1703.00676 (2017) - [i24]Christopher Morris, Kristian Kersting, Petra Mutzel:
Global Weisfeiler-Lehman Graph Kernels. CoRR abs/1703.02379 (2017) - [i23]Alejandro Molina, Alexander Munteanu, Kristian Kersting:
Coresets for Dependency Networks. CoRR abs/1710.03285 (2017) - [i22]Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting:
Sum-Product Networks for Hybrid Domains. CoRR abs/1710.03297 (2017) - 2016
- [i21]Martin Mladenov, Vaishak Belle, Kristian Kersting:
The Symbolic Interior Point Method. CoRR abs/1605.08187 (2016) - [i20]Piotr Szymanski, Tomasz Kajdanowicz, Kristian Kersting:
How is a data-driven approach better than random choice in label space division for multi-label classification? CoRR abs/1606.02346 (2016) - [i19]Martin Mladenov, Leonard Kleinhans, Kristian Kersting:
Lifted Convex Quadratic Programming. CoRR abs/1606.04486 (2016) - [i18]Elena Erdmann, Karin Boczek, Lars Koppers, Gerret von Nordheim, Christian Pölitz, Alejandro Molina, Katharina Morik, Henrik Müller, Jörg Rahnenführer, Kristian Kersting:
Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage. CoRR abs/1606.05110 (2016) - [i17]Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel:
Faster Kernels for Graphs with Continuous Attributes via Hashing. CoRR abs/1610.00064 (2016) - 2015
- [i16]Christian Bauckhage, Kristian Kersting, Fabian Hadiji:
Maximum Entropy Models of Shortest Path and Outbreak Distributions in Networks. CoRR abs/1501.04232 (2015) - 2014
- [i15]Christian Bauckhage, Kristian Kersting:
Strong Regularities in Growth and Decline of Popularity of Social Media Services. CoRR abs/1406.6529 (2014) - [i14]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR abs/1407.0179 (2014) - [i13]Kristian Kersting, Martin Mladenov, Pavel Tokmakov:
Relational Linear Programs. CoRR abs/1410.3125 (2014) - [i12]Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting:
Propagation Kernels. CoRR abs/1410.3314 (2014) - [i11]Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt:
High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline. CoRR abs/1411.1108 (2014) - 2013
- [i10]Fabian Hadiji, Kristian Kersting, Christian Bauckhage, Babak Ahmadi:
GeoDBLP: Geo-Tagging DBLP for Mining the Sociology of Computer Science. CoRR abs/1304.7984 (2013) - [i9]Martin Grohe, Kristian Kersting, Martin Mladenov, Erkal Selman:
Dimension Reduction via Colour Refinement. CoRR abs/1307.5697 (2013) - [i8]Christian Bauckhage, Kristian Kersting:
Efficient Information Theoretic Clustering on Discrete Lattices. CoRR abs/1310.7114 (2013) - 2012
- [i7]Kristian Kersting, Babak Ahmadi, Sriraam Natarajan:
Counting Belief Propagation. CoRR abs/1205.2637 (2012) - [i6]Kristian Kersting, Tapani Raiko:
'Say EM' for Selecting Probabilistic Models for Logical Sequences. CoRR abs/1207.1353 (2012) - [i5]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
A Revised Publication Model for ECML PKDD. CoRR abs/1207.6324 (2012) - [i4]Mirwaes Wahabzada, Kristian Kersting, Christian Bauckhage, Christoph Römer, Agim Ballvora, Francisco Pinto, Uwe Rascher, Jens Leon, Lutz Ploemer:
Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants. CoRR abs/1210.4919 (2012) - 2011
- [i3]Luc De Raedt, Kristian Kersting, Tapani Raiko:
Logical Hidden Markov Models. CoRR abs/1109.2148 (2011) - 2007
- [i2]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen H. Muggleton:
07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 - 2001
- [i1]Kristian Kersting, Luc De Raedt:
Bayesian Logic Programs. CoRR cs.AI/0111058 (2001)
Coauthor Index
[b3] [b2] [j69] [j59] [j44] [j33] [j30] [j29] [j28] [j26] [j25] [j21] [j17] [j11] [c221] [c219] [c203] [c198] [c186] [c178] [c165] [c160] [c155] [c150] [c143] [c140] [c139] [c135] [c132] [c131] [c128] [c127] [c125] [c124] [c116] [c115] [c113] [c108] [c106] [c105] [c103] [c100] [c99] [c95] [c93] [c91] [c86] [c82] [c77] [c76] [c68] [c65] [c57] [c52] [c44] [c34] [c29] [e4] [i144] [i78] [i61] [i52] [i36] [i27] [i22] [i7]
[j71] [j67] [j65] [j61] [j53] [j49] [j43] [c220] [c218] [c217] [c213] [c209] [c208] [c207] [c199] [c196] [c195] [c184] [c182] [c172] [c170] [c159] [i154] [i146] [i142] [i141] [i139] [i138] [i134] [i133] [i118] [i112] [i110] [i106] [i104] [i103] [i93] [i91] [i88] [i86] [i85] [i82] [i79] [i77] [i67] [i63] [i56] [i55] [i50] [i49] [i40] [i34] [i31]
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