Bauer, Stefan

68 publications

ICLRW 2025 Breaking the Likelihood--Quality Trade-Off in Diffusion Models by Merging Pretrained Experts Yasin Esfandiari, Stefan Bauer, Sebastian U Stich, Andrea Dittadi

TMLR 2025 Double Machine Learning Based Structure Identification from Temporal Data Emmanouil Angelis, Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Stefan Bauer

ICLRW 2025 Evolving RL: Discovering New Activation Functions Using LLMs Kalyan Varma Nadimpalli, Shashank Reddy Chirra, Pradeep Varakantham, Stefan Bauer

ICLR 2025 Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models Amir Mohammad Karimi Mamaghan, Samuele Papa, Karl Henrik Johansson, Stefan Bauer, Andrea Dittadi

ICLRW 2025 Learning Decision Trees as Amortized Structure Inference Mohammed Mahfoud, Ghait Boukachab, Michał Koziarski, Alex Hernández-García, Stefan Bauer, Yoshua Bengio, Nikolay Malkin

ICLRW 2025 Object-Centric Representations Generalize Better Compositionally with Less Compute Ferdinand Kapl, Amir Mohammad Karimi Mamaghan, Max Horn, Carsten Marr, Stefan Bauer, Andrea Dittadi

CVPRW 2025 Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation Leonard Waldmann, Ando Shah, Yi Wang, Nils Lehmann, Adam J. Stewart, Zhitong Xiong, Xiao Xiang Zhu, Stefan Bauer, John Chuang

NeurIPS 2025 Preference-Guided Diffusion for Multi-Objective Offline Optimization Yashas Annadani, Syrine Belakaria, Stefano Ermon, Stefan Bauer, Barbara E Engelhardt

NeurIPS 2024 Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster

ICMLW 2024 Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster

ICML 2024 Challenges and Considerations in the Evaluation of Bayesian Causal Discovery Amir Mohammad Karimi Mamaghan, Panagiotis Tigas, Karl Henrik Johansson, Yarin Gal, Yashas Annadani, Stefan Bauer

NeurIPS 2023 BayesDAG: Gradient-Based Posterior Inference for Causal Discovery Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong

ICMLW 2023 BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong

ICMLW 2023 Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio

ICLR 2023 Benchmarking Offline Reinforcement Learning on Real-Robot Hardware Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius

ICML 2023 DRCFS: Doubly Robust Causal Feature Selection Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Cristian R. Rojas, Stefan Bauer

ICML 2023 Differentiable Multi-Target Causal Bayesian Experimental Design Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

ICLRW 2023 Differentiable Multi-Target Causal Bayesian Experimental Design Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

ICMLW 2023 Diffusion Based Causal Representation Learning Amir Mohammad Karimi Mamaghan, Andrea Dittadi, Stefan Bauer, Francesco Quinzan

ICML 2023 Diffusion Based Representation Learning Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou

ICML 2023 DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab

TMLR 2023 Neural Causal Structure Discovery from Interventions Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio

ICLR 2023 Structure by Architecture: Structured Representations Without Regularization Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf

NeurIPS 2023 Trust Your $\nabla$: Gradient-Based Intervention Targeting for Causal Discovery Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś

ICML 2022 Adaptive Gaussian Process Change Point Detection Edoardo Caldarelli, Philippe Wenk, Stefan Bauer, Andreas Krause

UAI 2022 Bayesian Structure Learning with Generative Flow Networks Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio

ICLRW 2022 Bayesian Structure Learning with Generative Flow Networks Tristan Deleu, António Góis, Chris Chinenye Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio

TMLR 2022 Causal Feature Selection via Orthogonal Search Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve

ICLRW 2022 Compositional Multi-Object Reinforcement Learning with Linear Relation Networks Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello

TMLR 2022 Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

NeurIPSW 2022 Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

NeurIPS 2022 Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf

ICLRW 2022 From Points to Functions: Infinite-Dimensional Representations in Diffusion Models Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou

ICLR 2022 GeneDisco: A Benchmark for Experimental Design in Drug Discovery Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab

NeurIPS 2022 Interventions, Where and How? Experimental Design for Causal Models at Scale Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer

ICMLW 2022 Latent Variable Models for Bayesian Causal Discovery Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou

ICMLW 2022 On the Generalization and Adaption Performance of Causal Models Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke

ICLR 2022 The Role of Pretrained Representations for the OOD Generalization of RL Agents Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer

NeurIPSW 2022 Trust Your $\nabla$: Gradient-Based Intervention Targeting for Causal Discovery Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś

NeurIPSW 2021 Boxhead: A Dataset for Learning Hierarchical Representations Yukun Chen, Andrea Dittadi, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf

ICLR 2021 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer

ICML 2021 Function Contrastive Learning of Transferable Meta-Representations Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf

ICML 2021 On Disentangled Representations Learned from Correlated Data Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer

ICLR 2021 On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf

ICMLW 2021 Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer

ICMLW 2021 Representation Learning in Continuous-Time Score-Based Generative Models Korbinian Abstreiter, Stefan Bauer, Arash Mehrjou

ICLR 2021 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann

ICLR 2021 Spatially Structured Recurrent Modules Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf

NeurIPSW 2021 Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World Trifinger Arthur Allshire, Mayank Mittal, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Ankur Handa, Animesh Garg

AAAI 2020 A Commentary on the Unsupervised Learning of Disentangled Representations Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

JMLR 2020 A Sober Look at the Unsupervised Learning of Disentangled Representations and Their Evaluation Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

UAI 2020 Bayesian Online Prediction of Change Points Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters

ICLR 2020 Disentangling Factors of Variations Using Few Labels Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem

AAAI 2020 Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab, Lorenz Linhardt, Stefan Bauer, Joachim M. Buhmann, Walter Karlen

AAAI 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer

CoRL 2020 TriFinger: An Open-Source Robot for Learning Dexterity 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

ICML 2019 AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer

ICML 2019 Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

ICLRW 2019 Disentangled State Space Models: Unsupervised Learning of Dynamics Across Heterogeneous Environments Ðorđe Miladinović, Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer

ICLRW 2019 Disentangling Factors of Variations Using Few Labels Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar R¨¨ätsch, Bernhard Schölkopf, Olivier Bachem

AISTATS 2019 Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann

NeurIPS 2019 On the Fairness of Disentangled Representations Francesco Locatello, Gabriele Abbati, Thomas Rainforth, Stefan Bauer, Bernhard Schölkopf, Olivier Bachem

NeurIPS 2019 On the Transfer of Inductive Bias from Simulation to the Real World: A New Disentanglement Dataset Muhammad Waleed Gondal, Manuel Wuthrich, Djordje Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer

ICML 2019 Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter, Djordje Miladinovic, Bernhard Schölkopf, Stefan Bauer

NeurIPS 2018 Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models Alexander Neitz, Giambattista Parascandolo, Stefan Bauer, Bernhard Schölkopf

NeurIPS 2017 Efficient and Flexible Inference for Stochastic Systems Stefan Bauer, Nico S Gorbach, Djordje Miladinovic, Joachim M Buhmann

NeurIPS 2017 Scalable Variational Inference for Dynamical Systems Nico S Gorbach, Stefan Bauer, Joachim M Buhmann

ICML 2016 The Arrow of Time in Multivariate Time Series Stefan Bauer, Bernhard Schölkopf, Jonas Peters