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ORCIDDevendra Singh Dhami
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2020 – today
- 2025
[j11]Nika Strem, Devendra Singh Dhami, Benedikt Schmidt, Kristian Kersting:
Multimodal transformer for early alarm prediction. Eng. Appl. Artif. Intell. 139: 109643 (2025)- [j10]Nika Strem
, Devendra Singh Dhami, Benedikt Schmidt, Benjamin Klöpper, Kristian Kersting:
APT: Alarm Prediction Transformer. Expert Syst. Appl. 261: 125521 (2025) - [j9]Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
NeST: The neuro-symbolic transpiler. Int. J. Approx. Reason. 179: 109369 (2025) - [i52]Simon Kohaut, Benedict Flade, Daniel Ochs, Devendra Singh Dhami, Julian Eggert, Kristian Kersting:
Probabilistic Mission Design in Neuro-Symbolic Systems. CoRR abs/2501.01439 (2025) - [i51]Harsh Poonia, Felix Divo, Kristian Kersting, Devendra Singh Dhami:
Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data. CoRR abs/2502.09981 (2025) - [i50]Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting:
Scaling Probabilistic Circuits via Data Partitioning. CoRR abs/2503.08141 (2025) - 2024
- [j8]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Structural causal models reveal confounder bias in linear program modelling. Mach. Learn. 113(3): 1329-1349 (2024) - [j7]Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
Learning differentiable logic programs for abstract visual reasoning. Mach. Learn. 113(11): 8533-8584 (2024) - [j6]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) - [j5]Binon Teji, Swarup Roy, Devendra Singh Dhami, Dinabandhu Bhandari, Pietro Hiram Guzzi:
Graph Embedding Techniques for Predicting Missing Links in Biological Networks: An Empirical Evaluation. IEEE Trans. Emerg. Top. Comput. 12(1): 190-201 (2024) - [c26]Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG. ICLR 2024 - [c25]Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting:
DeiSAM: Segment Anything with Deictic Prompting. NeurIPS 2024 - [c24]Arseny Skryagin, Felix Divo, Mohammad Amin Ali, Devendra Singh Dhami, Kristian Kersting:
Graph Neural Networks Need Cluster-Normalize-Activate Modules. NeurIPS 2024 - [c23]Harsh Poonia, Moritz Willig, Zhongjie Yu, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami:
χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains. UAI 2024: 3004-3020 - [c22]Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting:
Pix2Code: Learning to Compose Neural Visual Concepts as Programs. UAI 2024: 3829-3852 - [i49]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) - [i48]Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting:
DeiSAM: Segment Anything with Deictic Prompting. CoRR abs/2402.14123 (2024) - [i47]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) - [i46]Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting:
Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Program. CoRR abs/2406.03454 (2024) - [i45]Jingyuan Sha, Hikaru Shindo, Quentin Delfosse, Kristian Kersting, Devendra Singh Dhami:
EXPIL: Explanatory Predicate Invention for Learning in Games. CoRR abs/2406.06107 (2024) - [i44]Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting:
Towards Probabilistic Clearance, Explanation and Optimization. CoRR abs/2406.15088 (2024) - [i43]Harsh Poonia, Moritz Willig, Zhongjie Yu, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami:
χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains. CoRR abs/2408.07545 (2024) - [i42]Hikaru Shindo, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting:
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning. CoRR abs/2410.11689 (2024) - [i41]Moritz Willig, Tim Nelson Tobiasch, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting:
Systems with Switching Causal Relations: A Meta-Causal Perspective. CoRR abs/2410.13054 (2024) - [i40]Maurice Kraus, Felix Divo, Devendra Singh Dhami, Kristian Kersting:
xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories. CoRR abs/2410.16928 (2024) - [i39]Antonia Wüst, Tim Nelson Tobiasch, Lukas Helff, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting:
Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad? CoRR abs/2410.19546 (2024) - [i38]Felix Divo, Eric Endress, Kevin Endler, Kristian Kersting, Devendra Singh Dhami:
Forecasting Company Fundamentals. CoRR abs/2411.05791 (2024) - [i37]Arseny Skryagin, Felix Divo, Mohammad Amin Ali, Devendra Singh Dhami, Kristian Kersting:
Graph Neural Networks Need Cluster-Normalize-Activate Modules. CoRR abs/2412.04064 (2024) - [i36]Arseny Skryagin, Daniel Ochs, Phillip Deibert, Simon Kohaut, Devendra Singh Dhami, Kristian Kersting:
Answer Set Networks: Casting Answer Set Programming into Deep Learning. CoRR abs/2412.14814 (2024) - [i35]Simon Kohaut, Felix Divo, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting:
The Constitutional Filter. CoRR abs/2412.18347 (2024) - [i34]Simon Kohaut, Benedict Flade, Julian Eggert, Devendra Singh Dhami, Kristian Kersting:
StaR Maps: Unveiling Uncertainty in Geospatial Relations. CoRR abs/2412.18356 (2024) - [i33]Simon Kohaut, Nikolas Hohmann, Sebastian Brulin, Benedict Flade, Julian Eggert, Markus Olhofer, Jürgen Adamy, Devendra Singh Dhami, Kristian Kersting:
Hybrid Many-Objective Optimization in Probabilistic Mission Design for Compliant and Effective UAV Routing. CoRR abs/2412.18514 (2024) - 2023
- [j4]Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Scalable Neural-Probabilistic Answer Set Programming. J. Artif. Intell. Res. 78: 579-617 (2023) - [j3]Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
αILP: thinking visual scenes as differentiable logic programs. Mach. Learn. 112(5): 1465-1497 (2023) - [j2]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Not All Causal Inference is the Same. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting:
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal. Trans. Mach. Learn. Res. 2023 (2023) - [c21]Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes:
Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program 2023: 1-10 - [c20]Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth:
Vision Relation Transformer for Unbiased Scene Graph Generation. ICCV 2023: 21825-21836 - [c19]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 - [c18]Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami:
Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes. NeSy 2023: 103-117 - [c17]Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. NeurIPS 2023 - [c16]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Do Not Marginalize Mechanisms, Rather Consolidate! NeurIPS 2023 - [e1]Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes:
AAAI Bridge Program on Continual Causality, 7-8 February 2023, Washington, DC, USA. Proceedings of Machine Learning Research 208, PMLR 2023 [contents] - [i32]Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. CoRR abs/2306.01439 (2023) - [i31]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) - [i30]Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Scalable Neural-Probabilistic Answer Set Programming. CoRR abs/2306.08397 (2023) - [i29]Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
Learning Differentiable Logic Programs for Abstract Visual Reasoning. CoRR abs/2307.00928 (2023) - [i28]Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth:
Vision Relation Transformer for Unbiased Scene Graph Generation. CoRR abs/2308.09472 (2023) - [i27]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) - [i26]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Do Not Marginalize Mechanisms, Rather Consolidate! CoRR abs/2310.08377 (2023) - 2022
- [c15]Mei Ling Fang, Devendra Singh Dhami, Kristian Kersting:
DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs. AIME 2022: 178-188 - [c14]Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. KR 2022 - [c13]Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting:
Neural-Probabilistic Answer Set Programming. KR 2022 - [c12]Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting:
Predictive Whittle networks for time series. UAI 2022: 2320-2330 - [i25]Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting:
Finding Structure and Causality in Linear Programs. CoRR abs/2203.15274 (2022) - [i24]David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Machines Explaining Linear Programs. CoRR abs/2206.07194 (2022) - [i23]Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation. CoRR abs/2206.07195 (2022) - [i22]Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Towards a Solution to Bongard Problems: A Causal Approach. CoRR abs/2206.07196 (2022) - [i21]Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami:
Attributions Beyond Neural Networks: The Linear Program Case. CoRR abs/2206.07203 (2022) - [i20]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Can Foundation Models Talk Causality? CoRR abs/2206.10591 (2022) - [i19]Jonas Seng, Pooja Prasad, Devendra Singh Dhami, Kristian Kersting:
HANF: Hyperparameter And Neural Architecture Search in Federated Learning. CoRR abs/2206.12342 (2022) - [i18]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) - [i17]Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Differentiable Meta logical Programming. CoRR abs/2211.11650 (2022) - [i16]Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting:
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges. CoRR abs/2212.12570 (2022) - 2021
- [c11]Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. AIME 2021: 252-257 - [c10]Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan:
Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning. COMAD/CODS 2021: 110-118 - [c9]Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan:
Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. ILP 2021: 95-110 - [c8]Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting:
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP 2021: 251-265 - [c7]Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan:
Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation. KR 2021: 247-257 - [c6]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 - [i15]Devendra Singh Dhami, Siwen Yan, Sriraam Natarajan:
Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN. CoRR abs/2102.07007 (2021) - [i14]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) - [i13]Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. CoRR abs/2103.10916 (2021) - [i12]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Intriguing Parameters of Structural Causal Models. CoRR abs/2105.12697 (2021) - [i11]Matej Zecevic, Devendra Singh Dhami, Petar Velickovic, Kristian Kersting:
Relating Graph Neural Networks to Structural Causal Models. CoRR abs/2109.04173 (2021) - [i10]Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting:
Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits. CoRR abs/2109.06587 (2021) - [i9]Matej Zecevic, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting:
Structural Causal Interpretation Theorem. CoRR abs/2110.02395 (2021) - [i8]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) - [i7]Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Neuro-Symbolic Forward Reasoning. CoRR abs/2110.09383 (2021) - [i6]Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
On the Tractability of Neural Causal Inference. CoRR abs/2110.12052 (2021) - [i5]Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
The Causal Loss: Driving Correlation to Imply Causation. CoRR abs/2110.12066 (2021) - 2020
- [c5]Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan:
The Curious Case of Stacking Boosted Relational Dependency Networks. ICBINB@NeurIPS 2020: 33-42 - [c4]Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan:
Knowledge Intensive Learning of Generative Adversarial Networks. KiML@KDD 2020: 10-16 - [i4]Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan:
Non-Parametric Learning of Gaifman Models. CoRR abs/2001.00528 (2020)
2010 – 2019
- 2019
- [c3]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 - [i3]Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan:
Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice. CoRR abs/1904.06950 (2019) - [i2]Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan:
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice. CoRR abs/1906.01432 (2019) - [i1]Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Molecular Structure Images. CoRR abs/1911.06356 (2019) - 2017
- [c2]Devendra Singh Dhami, David Leake, Sriraam Natarajan:
Knowledge-Based Morphological Classification of Galaxies from Vision Features. AAAI Workshops 2017 - [c1]Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan:
Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. AIME 2017: 332-337
Coauthor Index
[j11] [j10] [j9] [i52] [i51] [i50] [j8] [j7] [j6] [c26] [c25] [c24] [c23] [c22] [i49] [i48] [i47] [i46] [i45] [i44] [i43] [i42] [i41] [i40] [i39] [i38] [i37] [i36] [i35] [i34] [i33] [j4] [j3] [j2] [j1] [c20] [c19] [c18] [c17] [c16] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [c15] [c14] [c13] [c12] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [c8] [c6] [i14] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [c3]
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last updated on 2025-04-14 21:11 CEST by the dblp team
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