Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model. - Stefan Bauer; Lutz-Peter Nolte; Mauricio Reyes 001 (ISBI, 2011)

Fully Automatic Segmentation of Brain Tumor Images Using Support Vector Machine Classification in Combination with Hierarchical Conditional Random Field Regularization. - Stefan Bauer; Lutz-Peter Nolte; Mauricio Reyes 001 (MICCAI (3), 2011)

Das vernetzte Fahrzeug - Herausforderungen für die IT. - Stefan Bauer (Inform. Spektrum, 2011)

A Literature Review on Operational IT Risks and Regulations of Institutions in the Financial Service Sector. - Stefan Bauer (CONF-IRM, 2012)

Skull-stripping for Tumor-bearing Brain Images - Stefan Bauer; Lutz-Peter Nolte; Mauricio Reyes 001 (CoRR, 2012)

Multiscale Modeling for Image Analysis of Brain Tumor Studies. - Stefan Bauer; Christian May; Dimitra D. Dionysiou; Georgios S. Stamatakos; Philippe Büchler; Mauricio Reyes 001 (IEEE Trans. Biomed. Eng., 2012)

IT operational risk awareness building in banking companies: A preliminary research design highlighting the importance of risk cultures and control systems. - Stefan Bauer; Edward W. N. Bernroider (CONF-IRM, 2013)

GNSS correction services for ITS applications a performance analysis of EGNOS and IGS. - Robin Streiter; Sven Bauer; Stefan Bauer; Gerd Wanielik (ITSC, 2013)

Integrated Spatio-Temporal Segmentation of Longitudinal Brain Tumor Imaging Studies. - Stefan Bauer; Jean Tessier; Oliver Krieter; Lutz-Peter Nolte; Mauricio Reyes 001 (MCV, 2013)

Integrated segmentation of brain tumor images for radiotherapy and neurosurgery. - Stefan Bauer; Huanxiang Lu; Christian May; Lutz-Peter Nolte; Philippe Büchler; Mauricio Reyes 001 (Int. J. Imaging Syst. Technol., 2013)

Acting together by mutual control: Evaluation of a multimodal interaction concept for cooperative driving. - Markus Zimmermann; Stefan Bauer; Niklas Lutteken; Iris M. Rothkirch; Klaus-Josef Bengler (CTS, 2014)

Towards automatic MRI volumetry for treatment selection in acute ischemic stroke patients. - Stefan Bauer; Pascal P. Gratz; Jan Gralla; Mauricio Reyes 001; Roland Wiest (EMBC, 2014)

Interactive segmentation of MR images from brain tumor patients. - Stefan Bauer; Nicole Porz; Raphael Meier; Alessia Pica; Johannes Slotboom; Roland Wiest; Mauricio Reyes 001 (ISBI, 2014)

Patient-Specific Semi-supervised Learning for Postoperative Brain Tumor Segmentation. - Raphael Meier; Stefan Bauer; Johannes Slotboom; Roland Wiest; Mauricio Reyes 001 (MICCAI (1), 2014)

Mind the Threat! A Qualitative Case Study on Information Security Awareness Programs in European Banks. - Stefan Bauer; Katharina Chudzikowski (AMCIS, 2015)

Numerical decomposition of symmetric linear systems. - Claus Danielson; Stefan Bauer (CDC, 2015)

The Effects of Awareness Programs on Information Security in Banks: The Roles of Protection Motivation and Monitoring. - Stefan Bauer; Edward W. N. Bernroider (HCI (22), 2015)

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). - Bjoern H. Menze; András Jakab; Stefan Bauer; Jayashree Kalpathy-Cramer; Keyvan Farahani; Justin S. Kirby; Yuliya Burren; Nicole Porz; Johannes Slotboom; Roland Wiest; Levente Lanczi; Elizabeth R. Gerstner; et al. (IEEE Trans. Medical Imaging, 2015)

Digital Innovation and the Becoming of an Organizational Identity. - Nikolaus Obwegeser; Stefan Bauer (HCI (21), 2016)

The Arrow of Time in Multivariate Time Series. - Stefan Bauer; Bernhard Schölkopf; Jonas Peters (ICML, 2016)

Corporate Accelerators: Transferring Technology Innovation to Incumbent Companies. - Stefan Bauer; Nikolaus Obwegeser; Zlatko Avdagic (MCIS, 2016)

Multi-Organ Cancer Classification and Survival Analysis. - Stefan Bauer; Nicolas Carion; Peter J. Schüffler; Thomas J. Fuchs; Peter J. Wild; Joachim M. Buhmann (CoRR, 2016)

Model Selection for Gaussian Process Regression. - Nico S. Gorbach; Andrew An Bian; Benjamin Fischer; Stefan Bauer; Joachim M. Buhmann (GCPR, 2017)

MRI-Based Surgical Planning for Lumbar Spinal Stenosis. - Gabriele Abbati; Stefan Bauer; Sebastian Winklhofer; Peter J. Schüffler; Ulrike Held; Jakob M. Burgstaller; Johann Steurer; Joachim M. Buhmann (MICCAI (3), 2017)

Efficient and Flexible Inference for Stochastic Systems. - Stefan Bauer; Nico S. Gorbach; Ðorðe Miladinovic; Joachim M. Buhmann (NIPS, 2017)

Scalable Variational Inference for Dynamical Systems. - Nico S. Gorbach; Stefan Bauer; Joachim M. Buhmann (NIPS, 2017)

Prevention is better than cure! Designing information security awareness programs to overcome users' non-compliance with information security policies in banks. - Stefan Bauer; Edward W. N. Bernroider; Katharina Chudzikowski (Comput. Secur., 2017)

From Information Security Awareness to Reasoned Compliant Action: Analyzing Information Security Policy Compliance in a Large Banking Organization. - Stefan Bauer; Edward W. N. Bernroider (Data Base, 2017)

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

Identifying Causal Structure in Large-Scale Kinetic Systems. - Niklas Pfister; Stefan Bauer; Jonas Peters (CoRR, 2018)

Interventional Robustness of Deep Latent Variable Models. - Raphael Suter; Ðorðe Miladinovic; Stefan Bauer; Bernhard Schölkopf (CoRR, 2018)

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge. - Spyridon Bakas; Mauricio Reyes 001; András Jakab; Stefan Bauer; Markus Rempfler; Alessandro Crimi; Russell Takeshi Shinohara; Christoph Berger; Sung Min Ha; Martin Rozycki; Marcel Prastawa; Esther Alberts; et al. (CoRR, 2018)

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. - Francesco Locatello; Stefan Bauer; Mario Lucic; Sylvain Gelly; Bernhard Schölkopf; Olivier Bachem (CoRR, 2018)

Statistical Inference in Dynamical Systems. - Stefan Bauer (2018)

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 001; Joachim M. Buhmann (AISTATS, 2019)

Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments. - Ðorðe Miladinovic; Muhammad Waleed Gondal; Bernhard Schölkopf; Joachim M. Buhmann; Stefan Bauer (DGS@ICLR, 2019)

AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. - Gabriele Abbati; Philippe Wenk; Michael A. Osborne; Andreas Krause 001; Bernhard Schölkopf; Stefan Bauer (ICML, 2019)

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. - Francesco Locatello; Stefan Bauer; Mario Lucic; Gunnar Rätsch; Sylvain Gelly; Bernhard Schölkopf; Olivier Bachem (ICML, 2019)

Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness. - Raphael Suter; Ðorðe Miladinovic; Bernhard Schölkopf; Stefan Bauer (ICML, 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 (NeurIPS, 2019)

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

Multidimensional Contrast Limited Adaptive Histogram Equalization. - Vincent Stimper; Stefan Bauer; Ralph Ernstorfer; Bernhard Schölkopf; Rui Patrick Xian (IEEE Access, 2019)

Bayesian Online Detection and Prediction of Change Points. - Diego Agudelo-España; Sebastián Gómez-González; Stefan Bauer; Bernhard Schölkopf; Jan Peters 001 (CoRR, 2019)

Disentangling Factors of Variation Using Few Labels. - Francesco Locatello; Michael Tschannen; Stefan Bauer; Gunnar Rätsch; Bernhard Schölkopf; Olivier Bachem (CoRR, 2019)

Disentangled State Space Representations. - Ðorðe Miladinovic; Muhammad Waleed Gondal; Bernhard Schölkopf; Joachim M. Buhmann; Stefan Bauer (CoRR, 2019)

Learning Neural Causal Models from Unknown Interventions. - Nan Rosemary Ke; Olexa Bilaniuk; Anirudh Goyal; Stefan Bauer; Hugo Larochelle; Chris Pal; Yoshua Bengio (CoRR, 2019)

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. - 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 (PLoS Comput. Biol., 2019)

A Commentary on the Unsupervised Learning of Disentangled Representations. - Francesco Locatello; Stefan Bauer; Mario Lucic; Gunnar Rätsch; Sylvain Gelly; 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 001; Stefan Bauer (AAAI, 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; et al. (CoRL, 2020)

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

A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. - Diego Agudelo-España; Andrii Zadaianchuk; Philippe Wenk; Aditya Garg; Joel Akpo; Felix Grimminger; Julian Viereck; Maximilien Naveau; Ludovic Righetti; Georg Martius; Andreas Krause 001; Bernhard Schölkopf; et al. (ICRA, 2020)

Bayesian Online Prediction of Change Points. - Diego Agudelo-España; Sebastián Gómez-González; Stefan Bauer; Bernhard Schölkopf; Jan Peters 001 (UAI, 2020)

SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives. - Emmanouil Angelis; Philippe Wenk; Bernhard Schölkopf; Stefan Bauer; Andreas Krause 001 (CoRR, 2020)

predCOVID-19: A Systematic Study of Clinical Predictive Models for Coronavirus Disease 2019. - Patrick Schwab; August DuMont Schütte; Benedikt Dietz; Stefan Bauer (CoRR, 2020)

Structural Autoencoders Improve Representations for Generation and Transfer. - Felix Leeb; Yashas Annadani; Stefan Bauer; Bernhard Schölkopf (CoRR, 2020)

Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. - Frederik Träuble; Elliot Creager; Niki Kilbertus; Anirudh Goyal; Francesco Locatello; Bernhard Schölkopf; Stefan Bauer (CoRR, 2020)

S2RMs: Spatially Structured Recurrent Modules. - Nasim Rahaman; Anirudh Goyal; Muhammad Waleed Gondal; Manuel Wuthrich; Stefan Bauer; Yash Sharma 001; Yoshua Bengio; Bernhard Schölkopf (CoRR, 2020)

TriFinger: An Open-Source Robot for Learning Dexterity. - Manuel Wüthrich; Felix Widmaier; Felix Grimminger; Joel Akpo; Shruti Joshi; Vaibhav Agrawal; Bilal Hammoud; Majid Khadiv; Miroslav Bogdanovic; Vincent Berenz; Julian Viereck; Maximilien Naveau; et al. (CoRR, 2020)

Real-time Prediction of COVID-19 related Mortality using Electronic Health Records. - Patrick Schwab; Arash Mehrjou; Sonali Parbhoo; Leo Anthony Celi; Jürgen Hetzel; Markus Hofer; Bernhard Schölkopf; Stefan Bauer (CoRR, 2020)

Function Contrastive Learning of Transferable Representations. - Muhammad Waleed Gondal; Shruti Joshi; Nasim Rahaman; Stefan Bauer; Manuel Wüthrich; Bernhard Schölkopf (CoRR, 2020)

A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. - Francesco Locatello; Stefan Bauer; Mario Lucic; Gunnar Rätsch; Sylvain Gelly; Bernhard Schölkopf; Olivier Bachem (J. Mach. Learn. Res., 2020)

Automatic Training Set Compilation With Multisource Geodata for DTM Generation From the TanDEM-X DSM. - Christian Geiß; Patrick Aravena Pelizari; Stefan Bauer; Andreas Schmitt; Hannes Taubenböck (IEEE Geosci. Remote. Sens. Lett., 2020)

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 (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 (ICLR, 2021)

Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. - Ðorðe Miladinovic; Aleksandar Stanic; 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 001; Yoshua Bengio; Bernhard Schölkopf (ICLR, 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 (ICML, 2021)

Real Robot Challenge: A Robotics Competition in the Cloud. - Stefan Bauer; Manuel Wüthrich; Felix Widmaier; Annika Buchholz; Sebastian Stark; Anirudh Goyal; Thomas Steinbrenner; Joel Akpo; Shruti Joshi; Vincent Berenz; Vaibhav Agrawal; Niklas Funk; et al. (NeurIPS (Competition and Demos), 2021)

Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World. - 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; et al. (NeurIPS (Competition and Demos), 2021)

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. - Nan Rosemary Ke; Aniket Didolkar; Sarthak Mittal; Anirudh Goyal; Guillaume Lajoie; Stefan Bauer; Danilo Jimenez Rezende; Michael Mozer; Yoshua Bengio; Chris Pal (NeurIPS Datasets and Benchmarks, 2021)

Towards Causal Representation Learning. - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (CoRR, 2021)

NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments. - Sonali Parbhoo; Stefan Bauer; Patrick Schwab (CoRR, 2021)

Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases. - Arash Mehrjou; Ashkan Soleymani; Amin Abyaneh; Bernhard Schölkopf; Stefan Bauer (CoRR, 2021)

Representation Learning in Continuous-Time Score-Based Generative Models. - Korbinian Abstreiter; Stefan Bauer; Arash Mehrjou (CoRR, 2021)

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. - Yashas Annadani; Jonas Rothfuss; Alexandre Lacoste; Nino Scherrer; Anirudh Goyal; Yoshua Bengio; Stefan Bauer (CoRR, 2021)

Interventional Assays for the Latent Space of Autoencoders. - Felix Leeb; Stefan Bauer; Bernhard Schölkopf (CoRR, 2021)

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. - Andrea Dittadi; Frederik Träuble; Manuel Wüthrich; Felix Widmaier; Peter V. Gehler; Ole Winther; Francesco Locatello; Olivier Bachem; Bernhard Schölkopf; Stefan Bauer (CoRR, 2021)

Learning Neural Causal Models with Active Interventions. - Nino Scherrer; Olexa Bilaniuk; Yashas Annadani; Anirudh Goyal; Patrick Schwab; Bernhard Schölkopf; Michael C. Mozer; Yoshua Bengio; Stefan Bauer; Nan Rosemary Ke (CoRR, 2021)

A Robot Cluster for Reproducible Research in Dexterous Manipulation. - Stefan Bauer; Felix Widmaier; Manuel Wüthrich; Niklas Funk; Julen Urain De Jesus; Jan Peters 001; Joe Watson; Claire Chen; Krishnan Srinivasan; Junwu Zhang; Jeffrey Zhang 005; Matthew R. Walter; et al. (CoRR, 2021)

Boxhead: A Dataset for Learning Hierarchical Representations. - Yukun Chen; Frederik Träuble; Andrea Dittadi; Stefan Bauer; Bernhard Schölkopf (CoRR, 2021)

Overcoming barriers to data sharing with medical image generation: a comprehensive evaluation. - August DuMont Schütte; Jürgen Hetzel; Sergios Gatidis; Tobias Hepp 002; Benedikt Dietz; Stefan Bauer; Patrick Schwab (npj Digit. Medicine, 2021)

Toward Causal Representation Learning. - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (Proc. IEEE, 2021)

Causal Models for Dynamical Systems. - Jonas Peters; Stefan Bauer; Niklas Pfister (Probabilistic and Causal Inference, 2022)

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

Adaptive Gaussian Process Change Point Detection. - Edoardo Caldarelli; Philippe Wenk; Stefan Bauer; Andreas Krause 001 (ICML, 2022)

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 Wüthrich; Stefan Bauer; Ankur Handa; Animesh Garg (IROS, 2022)

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

Bayesian structure learning with generative flow networks. - Tristan Deleu; António Góis; Chris Emezue; Mansi Rankawat; Simon Lacoste-Julien; Stefan Bauer; Yoshua Bengio (UAI, 2022)

Selection of unlabeled source domains for domain adaptation in remote sensing. - Christian Geiß; Alexander Rabuske; Patrick Aravena Pelizari; Stefan Bauer; Hannes Taubenböck (Array, 2022)

Physical Derivatives: Computing policy gradients by physical forward-propagation. - Arash Mehrjou; Ashkan Soleymani; Stefan Bauer; Bernhard Schölkopf (CoRR, 2022)

Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. - Simon Bing; Andrea Dittadi; Stefan Bauer; Patrick Schwab (CoRR, 2022)

Compositional Multi-Object Reinforcement Learning with Linear Relation Networks. - Davide Mambelli; Frederik Träuble; Stefan Bauer; Bernhard Schölkopf; Francesco Locatello (CoRR, 2022)

Federated Learning in Multi-Center Critical Care Research: A Systematic Case Study using the eICU Database. - Arash Mehrjou; Ashkan Soleymani; Annika Buchholz; Jürgen Hetzel; Patrick Schwab; Stefan Bauer (CoRR, 2022)

On the Generalization and Adaption Performance of Causal Models. - Nino Scherrer; Anirudh Goyal; Stefan Bauer; Yoshua Bengio; Nan Rosemary Ke (CoRR, 2022)

Invariant Causal Mechanisms through Distribution Matching. - Mathieu Chevalley; Charlotte Bunne; Andreas Krause 001; Stefan Bauer (CoRR, 2022)

Latent Variable Models for Bayesian Causal Discovery. - Jithendaraa Subramanian; Yashas Annadani; Ivaxi Sheth; Stefan Bauer; Derek Nowrouzezahrai; Samira Ebrahimi Kahou (CoRR, 2022)

Predicting the protein-ligand affinity from molecular dynamics trajectories. - Yaosen Min; Ye Wei; Peizhuo Wang; Nian Wu; Stefan Bauer; Shuxin Zheng; Yu Shi; Yingheng Wang; Dan Zhao 004; Ji Wu 002; Jianyang Zeng 001 (CoRR, 2022)

Learning Latent Structural Causal Models. - Jithendaraa Subramanian; Yashas Annadani; Ivaxi Sheth; Nan Rosemary Ke; Tristan Deleu; Stefan Bauer; Derek Nowrouzezahrai; Samira Ebrahimi Kahou (CoRR, 2022)

From Points to Functions: Infinite-dimensional Representations in Diffusion Models. - Sarthak Mittal; Guillaume Lajoie; Stefan Bauer; Arash Mehrjou (CoRR, 2022)

FED-CD: Federated Causal Discovery from Interventional and Observational Data. - Amin Abyaneh; Nino Scherrer; Patrick Schwab; Stefan Bauer; Bernhard Schölkopf; Arash Mehrjou (CoRR, 2022)

Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. - 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; et al. (IEEE Robotics Autom. Lett., 2022)

Diffusion Models for Video Prediction and Infilling. - Tobias Höppe; Arash Mehrjou; Stefan Bauer; Didrik Nielsen; Andrea Dittadi (Trans. Mach. Learn. Res., 2022)

Causal Feature Selection via Orthogonal Search. - Ashkan Soleymani; Anant Raj; Stefan Bauer; Bernhard Schölkopf; Michel Besserve (Trans. Mach. Learn. Res., 2022)

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

Structure by Architecture: Structured Representations without Regularization. - Felix Leeb; Giulia Lanzillotta; Yashas Annadani; Michel Besserve; Stefan Bauer; Bernhard Schölkopf (ICLR, 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 (ICML, 2023)

Diffusion Based Representation Learning. - Sarthak Mittal; Korbinian Abstreiter; Stefan Bauer; Bernhard Schölkopf; Arash Mehrjou (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 001; Stefan Bauer (ICML, 2023)

BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. - Yashas Annadani; Nick Pawlowski; Joel Jennings; Stefan Bauer; Cheng Zhang 005; Wenbo Gong 001 (NeurIPS, 2023)

Trust Your 𝛁: Gradient-based Intervention Targeting for Causal Discovery. - Mateusz Olko; Michal Zajac 005; Aleksandra Nowak 001; Nino Scherrer; Yashas Annadani; Stefan Bauer; Lukasz Kucinski; Piotr Milos (NeurIPS, 2023)

Understanding Causality with Large Language Models: Feasibility and Opportunities. - Cheng Zhang 005; Stefan Bauer; Paul Bennett; Jiangfeng Gao; Wenbo Gong 001; Agrin Hilmkil; Joel Jennings; Chao Ma 019; Tom Minka; Nick Pawlowski; James Vaughan (CoRR, 2023)

Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. - Chris Chinenye Emezue; Alexandre Drouin; Tristan Deleu; Stefan Bauer; Yoshua Bengio (CoRR, 2023)

BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. - Yashas Annadani; Nick Pawlowski; Joel Jennings; Stefan Bauer; Cheng Zhang 005; Wenbo Gong 001 (CoRR, 2023)

Causal machine learning for single-cell genomics. - Alejandro Tejada-Lapuerta; Paul Bertin; Stefan Bauer; Hananeh Aliee; Yoshua Bengio; Fabian J. Theis (CoRR, 2023)

Doubly Robust Structure Identification from Temporal Data. - Emmanouil Angelis; Francesco Quinzan; Ashkan Soleymani; Patrick Jaillet; Stefan Bauer (CoRR, 2023)

A machine learning route between band mapping and band structure. - 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 (Nat. Comput. Sci., 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 (Trans. Mach. Learn. Res., 2023)

Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases. - Arash Mehrjou; Ashkan Soleymani; Amin Abyaneh; Samir Bhatt; Bernhard Schölkopf; Stefan Bauer (PLoS Comput. Biol., 2023)

Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward-based tasks. - 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 (Expert Syst. J. Knowl. Eng., 2023)

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 (ICML, 2024)

Amortized Active Causal Induction with Deep Reinforcement Learning. - Yashas Annadani; Panagiotis Tigas; Stefan Bauer; Adam Foster 001 (NeurIPS, 2024)

The Essential Role of Causality in Foundation World Models for Embodied AI. - Tarun Gupta 002; Wenbo Gong 001; Chao Ma 019; Nick Pawlowski; Agrin Hilmkil; Meyer Scetbon; Ade Famoti; Ashley Juan Llorens; Jianfeng Gao 001; Stefan Bauer; Danica Kragic; Bernhard Schölkopf; et al. (CoRR, 2024)

Derivative-free tree optimization for complex systems. - Ye Wei; Bo Peng; Ruiwen Xie; Yangtao Chen; Yu Qin; Peng Wen; Stefan Bauer; Po-Yen Tung (CoRR, 2024)

Opportunities for machine learning in scientific discovery. - 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 (CoRR, 2024)

Causal machine learning for predicting treatment outcomes. - Stefan Feuerriegel; Dennis Frauen; Valentyn Melnychuk; Jonas Schweisthal; Konstantin Hess; Alicia Curth; Stefan Bauer; Niki Kilbertus; Isaac S. Kohane; Mihaela van der Schaar (CoRR, 2024)

An Exploration of Hackathons as Time Intense and Collaborative Forms of Crowdsourcing. - Michela Beretta; Nikolaus Obwegeser; Stefan Bauer (IEEE Trans. Engineering Management, 2024)

Diffusion-Based Causal Representation Learning. - Amir Mohammad Karimi-Mamaghan; Andrea Dittadi; Stefan Bauer; Karl Henrik Johansson; Francesco Quinzan (Entropy, 2024)

Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation. - Leonard Waldmann; Ando Shah; Yi Wang 072; Nils Lehmann; Adam J. Stewart; Zhitong Xiong; Xiao Xiang Zhu 001; Stefan Bauer; John Chuang (CVPR Workshops, 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 (ICLR, 2025)

Robustness tests for biomedical foundation models should tailor to specification. - R. Patrick Xian; Noah R. Baker; Tom David; Qiming Cui; A Jay Holmgren; Stefan Bauer; Madhumita Sushil; Reza Abbasi-Asl (CoRR, 2025)

Measuring temporal effects of agent knowledge by date-controlled tool use. - R. Patrick Xian; Qiming Cui; Stefan Bauer; Reza Abbasi-Asl (CoRR, 2025)

Learning Decision Trees as Amortized Structure Inference. - Mohammed Mahfoud; Ghait Boukachab; Michal Koziarski; Alex Hernández-García; Stefan Bauer; Yoshua Bengio; Nikolay Malkin (CoRR, 2025)

Preference-Guided Diffusion for Multi-Objective Offline Optimization. - Yashas Annadani; Syrine Belakaria; Stefano Ermon; Stefan Bauer; Barbara E. Engelhardt (CoRR, 2025)

Causal Bayesian Optimization with Unknown Graphs. - Jean Durand; Yashas Annadani; Stefan Bauer; Sonali Parbhoo (CoRR, 2025)

A scalable gene network model of regulatory dynamics in single cells. - Paul Bertin; Joseph D. Viviano; Alejandro Tejada-Lapuerta; Weixu Wang; Stefan Bauer; Fabian J. Theis; Yoshua Bengio (CoRR, 2025)

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis. - Haroui Ma; Francesco Quinzan; Theresa Willem; Stefan Bauer (CoRR, 2025)

Minimum-Excess-Work Guidance. - Christopher Kolloff; Tobias Höppe; Emmanouil Angelis; Mathias Jacob Schreiner; Stefan Bauer; Andrea Dittadi; Simon Olsson (CoRR, 2025)