default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDStefan Bauer
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j22]Amir Mohammad Karimi-Mamaghan
, Andrea Dittadi, Stefan Bauer, Karl Henrik Johansson, Francesco Quinzan:
Diffusion-Based Causal Representation Learning. Entropy 26(7): 556 (2024)- [j21]Michela Beretta, Nikolaus Obwegeser, Stefan Bauer:
An Exploration of Hackathons as Time Intense and Collaborative Forms of Crowdsourcing. IEEE Trans. Engineering Management 71: 2403-2417 (2024) - [c61]Amir Mohammad Karimi-Mamaghan, Panagiotis Tigas, Karl Henrik Johansson, Yarin Gal, Yashas Annadani, Stefan Bauer:
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery. ICML 2024 - [i80]Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang:
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR abs/2402.06665 (2024) - [i79]Ye Wei, Bo Peng, Ruiwen Xie, Yangtao Chen, Yu Qin, Peng Wen, Stefan Bauer, Po-Yen Tung:
Derivative-free tree optimization for complex systems. CoRR abs/2404.04062 (2024) - [i78]Ricardo Vinuesa, Jean Rabault, Hossein Azizpour, Stefan Bauer, Bingni W. Brunton, Arne Elofsson, Elias Jarlebring, Hedvig Kjellström, Stefano Markidis, David Marlevi, Paola Cinnella, Steven L. Brunton:
Opportunities for machine learning in scientific discovery. CoRR abs/2405.04161 (2024) - [i77]Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster:
Amortized Active Causal Induction with Deep Reinforcement Learning. CoRR abs/2405.16718 (2024) - [i76]Amir Mohammad Karimi-Mamaghan, Panagiotis Tigas, Karl Henrik Johansson, Yarin Gal, Yashas Annadani, Stefan Bauer:
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery. CoRR abs/2406.03209 (2024) - [i75]Amir Mohammad Karimi-Mamaghan, Samuele Papa, Karl Henrik Johansson, Stefan Bauer, Andrea Dittadi:
Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models. CoRR abs/2407.15589 (2024) - [i74]Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal, Konstantin Hess, Alicia Curth, Stefan Bauer, Niki Kilbertus, Isaac S. Kohane, Mihaela van der Schaar:
Causal machine learning for predicting treatment outcomes. CoRR abs/2410.08770 (2024) - 2023
- [j20]Qiang Wang, Francisco Roldan Sanchez, Robert McCarthy, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Manuel Wüthrich, Felix Widmaier, Stefan Bauer, Stephen J. Redmond:
Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward-based tasks. Expert Syst. J. Knowl. Eng. 40(6) (2023) - [j19]R. Patrick Xian, Vincent Stimper, Marios Zacharias, Maciej Dendzik, Shuo Dong, Samuel Beaulieu, Bernhard Schölkopf, Martin Wolf, Laurenz Rettig, Christian Carbogno, Stefan Bauer, Ralph Ernstorfer:
A machine learning route between band mapping and band structure. Nat. Comput. Sci. 3(1): 101-114 (2023) - [j18]Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Samir Bhatt, Bernhard Schölkopf, Stefan Bauer:
Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases. PLoS Comput. Biol. 19(1) (2023) - [j17]Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio:
Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. 2023 (2023) - [c60]Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius:
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware. ICLR 2023 - [c59]Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf:
Structure by Architecture: Structured Representations without Regularization. ICLR 2023 - [c58]Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab:
DiscoBAX: Discovery of optimal intervention sets in genomic experiment design. ICML 2023: 23170-23189 - [c57]Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou:
Diffusion Based Representation Learning. ICML 2023: 24963-24982 - [c56]Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Cristian R. Rojas, Stefan Bauer:
DRCFS: Doubly Robust Causal Feature Selection. ICML 2023: 28468-28491 - [c55]Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer:
Differentiable Multi-Target Causal Bayesian Experimental Design. ICML 2023: 34263-34279 - [c54]Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. NeurIPS 2023 - [c53]Mateusz Olko, Michal Zajac, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Lukasz Kucinski, Piotr Milos:
Trust Your 𝛁: Gradient-based Intervention Targeting for Causal Discovery. NeurIPS 2023 - [i73]Yashas Annadani, Panagiotis Tigas, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer:
Differentiable Multi-Target Causal Bayesian Experimental Design. CoRR abs/2302.10607 (2023) - [i72]Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan:
Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR abs/2304.05524 (2023) - [i71]Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Cristian R. Rojas, Stefan Bauer:
DRCFS: Doubly Robust Causal Feature Selection. CoRR abs/2306.07024 (2023) - [i70]Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio:
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. CoRR abs/2307.04988 (2023) - [i69]Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. CoRR abs/2307.13917 (2023) - [i68]Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius:
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware. CoRR abs/2307.15690 (2023) - [i67]Nico Gürtler, Felix Widmaier, Cansu Sancaktar, Sebastian Blaes, Pavel Kolev, Stefan Bauer, Manuel Wüthrich, Markus Wulfmeier, Martin A. Riedmiller, Arthur Allshire, Qiang Wang, Robert McCarthy, Hangyeol Kim, Jongchan Baek, Wookyong Kwon, Shanliang Qian, Yasunori Toshimitsu, Mike Yan Michelis, Amirhossein Kazemipour, Arman Raayatsanati, Hehui Zheng, Barnabas Gavin Cangan, Bernhard Schölkopf, Georg Martius:
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World. CoRR abs/2308.07741 (2023) - [i66]Alejandro Tejada-Lapuerta, Paul Bertin, Stefan Bauer, Hananeh Aliee, Yoshua Bengio, Fabian J. Theis:
Causal machine learning for single-cell genomics. CoRR abs/2310.14935 (2023) - [i65]Amir Mohammad Karimi-Mamaghan, Andrea Dittadi, Stefan Bauer, Karl Henrik Johansson, Francesco Quinzan:
Diffusion Based Causal Representation Learning. CoRR abs/2311.05421 (2023) - [i64]Emmanouil Angelis, Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Stefan Bauer:
Doubly Robust Structure Identification from Temporal Data. CoRR abs/2311.06012 (2023) - [i63]Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab:
DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design. CoRR abs/2312.04064 (2023) - 2022
- [j16]Christian Geiß, Alexander Rabuske, Patrick Aravena Pelizari, Stefan Bauer, Hannes Taubenböck:
Selection of unlabeled source domains for domain adaptation in remote sensing. Array 15: 100233 (2022) - [j15]Niklas Funk, Charles B. Schaff, Rishabh Madan, Takuma Yoneda, Julen Urain De Jesus, Joe Watson, Ethan K. Gordon, Felix Widmaier, Stefan Bauer, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Matthew R. Walter, Jan Peters:
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. IEEE Robotics Autom. Lett. 7(1): 478-485 (2022) - [j14]Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi:
Diffusion Models for Video Prediction and Infilling. Trans. Mach. Learn. Res. 2022 (2022) - [j13]Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve:
Causal Feature Selection via Orthogonal Search. Trans. Mach. Learn. Res. 2022 (2022) - [c52]Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab:
GeneDisco: A Benchmark for Experimental Design in Drug Discovery. ICLR 2022 - [c51]Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR 2022 - [c50]Edoardo Caldarelli, Philippe Wenk, Stefan Bauer, Andreas Krause:
Adaptive Gaussian Process Change Point Detection. ICML 2022: 2542-2571 - [c49]Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, Animesh Garg:
Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger. IROS 2022: 11802-11809 - [c48]Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf:
Exploring the Latent Space of Autoencoders with Interventional Assays. NeurIPS 2022 - [c47]Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer:
Interventions, Where and How? Experimental Design for Causal Models at Scale. NeurIPS 2022 - [c46]Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio:
Bayesian structure learning with generative flow networks. UAI 2022: 518-528 - [p1]Jonas Peters, Stefan Bauer, Niklas Pfister:
Causal Models for Dynamical Systems. Probabilistic and Causal Inference 2022: 671-690 - [i62]Arash Mehrjou, Ashkan Soleymani, Stefan Bauer, Bernhard Schölkopf:
Physical Derivatives: Computing policy gradients by physical forward-propagation. CoRR abs/2201.05830 (2022) - [i61]Simon Bing, Andrea Dittadi, Stefan Bauer, Patrick Schwab:
Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. CoRR abs/2201.08186 (2022) - [i60]Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello:
Compositional Multi-Object Reinforcement Learning with Linear Relation Networks. CoRR abs/2201.13388 (2022) - [i59]Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio:
Bayesian Structure Learning with Generative Flow Networks. CoRR abs/2202.13903 (2022) - [i58]Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer:
Interventions, Where and How? Experimental Design for Causal Models at Scale. CoRR abs/2203.02016 (2022) - [i57]Arash Mehrjou, Ashkan Soleymani, Annika Buchholz, Jürgen Hetzel, Patrick Schwab, Stefan Bauer:
Federated Learning in Multi-Center Critical Care Research: A Systematic Case Study using the eICU Database. CoRR abs/2204.09328 (2022) - [i56]Qiang Wang, Francisco Roldan Sanchez, Robert McCarthy, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Manuel Wüthrich, Felix Widmaier, Stefan Bauer, Stephen J. Redmond:
Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks. CoRR abs/2205.09683 (2022) - [i55]Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke:
On the Generalization and Adaption Performance of Causal Models. CoRR abs/2206.04620 (2022) - [i54]Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi:
Diffusion Models for Video Prediction and Infilling. CoRR abs/2206.07696 (2022) - [i53]Mathieu Chevalley, Charlotte Bunne, Andreas Krause, Stefan Bauer:
Invariant Causal Mechanisms through Distribution Matching. CoRR abs/2206.11646 (2022) - [i52]Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou:
Latent Variable Models for Bayesian Causal Discovery. CoRR abs/2207.05723 (2022) - [i51]Yaosen Min, Ye Wei, Peizhuo Wang, Nian Wu, Stefan Bauer, Shuxin Zheng, Yu Shi, Yingheng Wang, Dan Zhao, Ji Wu, Jianyang Zeng:
Predicting the protein-ligand affinity from molecular dynamics trajectories. CoRR abs/2208.10230 (2022) - [i50]Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou:
Learning Latent Structural Causal Models. CoRR abs/2210.13583 (2022) - [i49]Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou:
From Points to Functions: Infinite-dimensional Representations in Diffusion Models. CoRR abs/2210.13774 (2022) - [i48]Amin Abyaneh, Nino Scherrer, Patrick Schwab, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou:
FED-CD: Federated Causal Discovery from Interventional and Observational Data. CoRR abs/2211.03846 (2022) - [i47]Mateusz Olko, Michal Zajac, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Lukasz Kucinski, Piotr Milos:
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery. CoRR abs/2211.13715 (2022) - 2021
- [j12]August DuMont Schütte, Jürgen Hetzel, Sergios Gatidis, Tobias Hepp, Benedikt Dietz, Stefan Bauer, Patrick Schwab:
Overcoming barriers to data sharing with medical image generation: a comprehensive evaluation. npj Digit. Medicine 4 (2021) - [j11]Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio:
Toward Causal Representation Learning. Proc. IEEE 109(5): 612-634 (2021) - [c45]Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer:
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. ICLR 2021 - [c44]Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf:
On the Transfer of Disentangled Representations in Realistic Settings. ICLR 2021 - [c43]Ðorðe Miladinovic, Aleksandar Stanic, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann:
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. ICLR 2021 - [c42]Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf:
Spatially Structured Recurrent Modules. ICLR 2021 - [c41]Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf:
Function Contrastive Learning of Transferable Meta-Representations. ICML 2021: 3755-3765 - [c40]Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer:
On Disentangled Representations Learned from Correlated Data. ICML 2021: 10401-10412 - [c39]Nico Gürtler, Felix Widmaier, Cansu Sancaktar, Sebastian Blaes, Pavel Kolev, Stefan Bauer, Manuel Wüthrich, Markus Wulfmeier, Martin A. Riedmiller, Arthur Allshire, Qiang Wang, Robert McCarthy, Hangyeol Kim, Jongchan Baek, Wookyong Kwon, Shanliang Qian, Yasunori Toshimitsu, Mike Yan Michelis, Amirhossein Kazemipour, Arman Raayatsanati, Hehui Zheng, Barnabas Gavin Cangan, Bernhard Schölkopf, Georg Martius:
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World. NeurIPS (Competition and Demos) 2021: 133-150 - [c38]Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vincent Berenz, Vaibhav Agrawal, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Takahiro Maeda, Harshit Sikchi, Jilong Wang, Qingfeng Yao, Shuyu Yang, Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Stephen J. Redmond, Bernhard Schölkopf:
Real Robot Challenge: A Robotics Competition in the Cloud. NeurIPS (Competition and Demos) 2021: 190-204 - [c37]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [i46]Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio:
Towards Causal Representation Learning. CoRR abs/2102.11107 (2021) - [i45]Djordje Miladinovic, Aleksandar Stanic, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann:
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. CoRR abs/2103.08877 (2021) - [i44]Sonali Parbhoo, Stefan Bauer, Patrick Schwab:
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments. CoRR abs/2103.11175 (2021) - [i43]Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Bernhard Schölkopf, Stefan Bauer:
Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases. CoRR abs/2103.15561 (2021) - [i42]Niklas Funk, Charles B. Schaff, Rishabh Madan, Takuma Yoneda, Julen Urain De Jesus, Joe Watson, Ethan K. Gordon, Felix Widmaier, Stefan Bauer, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Matthew R. Walter, Jan Peters:
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. CoRR abs/2105.02087 (2021) - [i41]Korbinian Abstreiter, Stefan Bauer, Arash Mehrjou:
Representation Learning in Continuous-Time Score-Based Generative Models. CoRR abs/2105.14257 (2021) - [i40]Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer:
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR abs/2106.07635 (2021) - [i39]Felix Leeb, Stefan Bauer, Bernhard Schölkopf:
Interventional Assays for the Latent Space of Autoencoders. CoRR abs/2106.16091 (2021) - [i38]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR abs/2107.00848 (2021) - [i37]Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer:
Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR abs/2107.05686 (2021) - [i36]Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, Animesh Garg:
Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger. CoRR abs/2108.09779 (2021) - [i35]Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke:
Learning Neural Causal Models with Active Interventions. CoRR abs/2109.02429 (2021) - [i34]Stefan Bauer, Felix Widmaier, Manuel Wüthrich, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Charles B. Schaff, Takahiro Maeda, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Annika Buchholz, Sebastian Stark, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bernhard Schölkopf:
A Robot Cluster for Reproducible Research in Dexterous Manipulation. CoRR abs/2109.10957 (2021) - [i33]Yukun Chen, Frederik Träuble, Andrea Dittadi, Stefan Bauer, Bernhard Schölkopf:
Boxhead: A Dataset for Learning Hierarchical Representations. CoRR abs/2110.03628 (2021) - [i32]Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab:
GeneDisco: A Benchmark for Experimental Design in Drug Discovery. CoRR abs/2110.11875 (2021) - 2020
- [j10]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. J. Mach. Learn. Res. 21: 209:1-209:62 (2020) - [j9]Christian Geiß, Patrick Aravena Pelizari, Stefan Bauer, Andreas Schmitt, Hannes Taubenböck:
Automatic Training Set Compilation With Multisource Geodata for DTM Generation From the TanDEM-X DSM. IEEE Geosci. Remote. Sens. Lett. 17(3): 456-460 (2020) - [c36]Patrick Schwab, Lorenz Linhardt, Stefan Bauer, Joachim M. Buhmann, Walter Karlen:
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves. AAAI 2020: 5612-5619 - [c35]Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer:
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI 2020: 6364-6371 - [c34]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Commentary on the Unsupervised Learning of Disentangled Representations. AAAI 2020: 13681-13684 - [c33]Manuel Wuthrich, Felix Widmaier, Felix Grimminger, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer:
TriFinger: An Open-Source Robot for Learning Dexterity. CoRL 2020: 1871-1882 - [c32]Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem:
Disentangling Factors of Variations Using Few Labels. ICLR 2020 - [c31]Diego Agudelo-España, Andrii Zadaianchuk, Philippe Wenk, Aditya Garg, Joel Akpo, Felix Grimminger, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Georg Martius, Andreas Krause, Bernhard Schölkopf, Stefan Bauer, Manuel Wüthrich:
A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. ICRA 2020: 8151-8157 - [c30]Diego Agudelo-España, Sebastián Gómez-González, Stefan Bauer, Bernhard Schölkopf, Jan Peters:
Bayesian Online Prediction of Change Points. UAI 2020: 320-329 - [i31]Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause:
SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives. CoRR abs/2003.02658 (2020) - [i30]Patrick Schwab, August DuMont Schütte, Benedikt Dietz, Stefan Bauer:
predCOVID-19: A Systematic Study of Clinical Predictive Models for Coronavirus Disease 2019. CoRR abs/2005.08302 (2020) - [i29]Felix Leeb, Yashas Annadani, Stefan Bauer, Bernhard Schölkopf:
Structural Autoencoders Improve Representations for Generation and Transfer. CoRR abs/2006.07796 (2020) - [i28]Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer:
Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. CoRR abs/2006.07886 (2020) - [i27]Anant Raj, Stefan Bauer, Ashkan Soleymani, Michel Besserve, Bernhard Schölkopf:
Causal Feature Selection via Orthogonal Search. CoRR abs/2007.02938 (2020) - [i26]Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf:
S2RMs: Spatially Structured Recurrent Modules. CoRR abs/2007.06533 (2020) - [i25]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Commentary on the Unsupervised Learning of Disentangled Representations. CoRR abs/2007.14184 (2020) - [i24]Manuel Wüthrich, Felix Widmaier, Felix Grimminger, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer:
TriFinger: An Open-Source Robot for Learning Dexterity. CoRR abs/2008.03596 (2020) - [i23]Patrick Schwab, Arash Mehrjou, Sonali Parbhoo, Leo Anthony Celi, Jürgen Hetzel, Markus Hofer, Bernhard Schölkopf, Stefan Bauer:
Real-time Prediction of COVID-19 related Mortality using Electronic Health Records. CoRR abs/2008.13412 (2020) - [i22]Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer:
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. CoRR abs/2010.04296 (2020) - [i21]Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wüthrich, Bernhard Schölkopf:
Function Contrastive Learning of Transferable Representations. CoRR abs/2010.07093 (2020) - [i20]Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf:
On the Transfer of Disentangled Representations in Realistic Settings. CoRR abs/2010.14407 (2020) - [i19]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. CoRR abs/2010.14766 (2020) - [i18]August DuMont Schütte, Jürgen Hetzel, Sergios Gatidis, Tobias Hepp, Benedikt Dietz, Stefan Bauer, Patrick Schwab:
Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation. CoRR abs/2012.03769 (2020)
2010 – 2019
- 2019
- [j8]Vincent Stimper, Stefan Bauer, Ralph Ernstorfer, Bernhard Schölkopf, Rui Patrick Xian:
Multidimensional Contrast Limited Adaptive Histogram Equalization. IEEE Access 7: 165437-165447 (2019) - [j7]Ðorðe Miladinovic, Christine Muheim, Stefan Bauer, Andrea Spinnler, Daniela Noain, Mojtaba Bandarabadi, Benjamin Gallusser, Gabriel Krummenacher, Christian R. Baumann, Antoine Adamantidis, Steven A. Brown, Joachim M. Buhmann:
SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. PLoS Comput. Biol. 15(4) (2019) - [c29]Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause,