Stefan Bauer

Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models ICLR 2025 Measuring temporal effects of agent knowledge by date-controlled tool use ACL 2025 Amortized Active Causal Induction with Deep Reinforcement Learning NeurIPS 2024 Challenges and Considerations in the Evaluation of Bayesian Causal Discovery ICML 2024 BayesDAG: Gradient-Based Posterior Inference for Causal Discovery NeurIPS 2023 Benchmarking Offline Reinforcement Learning on Real-Robot Hardware ICLR 2023 Differentiable Multi-Target Causal Bayesian Experimental Design ICML 2023 Diffusion Based Representation Learning ICML 2023 DiscoBAX: Discovery of optimal intervention sets in genomic experiment design ICML 2023 DRCFS: Doubly Robust Causal Feature Selection ICML 2023 Structure by Architecture: Structured Representations without Regularization ICLR 2023 Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery NeurIPS 2023 Adaptive Gaussian Process Change Point Detection ICML 2022 Bayesian structure learning with generative flow networks UAI 2022 Exploring the Latent Space of Autoencoders with Interventional Assays NeurIPS 2022 GeneDisco: A Benchmark for Experimental Design in Drug Discovery ICLR 2022 Interventions, Where and How? Experimental Design for Causal Models at Scale NeurIPS 2022 The Role of Pretrained Representations for the OOD Generalization of RL Agents ICLR 2022 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ICLR 2021 Function Contrastive Learning of Transferable Meta-Representations ICML 2021 On Disentangled Representations Learned from Correlated Data ICML 2021 On the Transfer of Disentangled Representations in Realistic Settings ICLR 2021 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling ICLR 2021 Spatially Structured Recurrent Modules ICLR 2021 A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation JMLR 2020 Bayesian Online Prediction of Change Points UAI 2020 Disentangling Factors of Variations Using Few Labels ICLR 2020 Learning Counterfactual Representations for Estimating Individual Dose-Response Curves AAAI 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems AAAI 2020 TriFinger: An Open-Source Robot for Learning Dexterity CoRL 2020 AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs ICML 2019 Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations ICML 2019 Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs AISTATS 2019 On the Fairness of Disentangled Representations NeurIPS 2019 On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset NeurIPS 2019 Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness ICML 2019 Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models NeurIPS 2018 Efficient and Flexible Inference for Stochastic Systems NeurIPS 2017 Scalable Variational Inference for Dynamical Systems NeurIPS 2017 The Arrow of Time in Multivariate Time Series ICML 2016