Bernhard Schölkopf

ORCID

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 571

Top Venues

Berlin Institute of Technology (PHD)

Education History

Berlin Institute of Technology

PHD

Publications

Alice Bizeul, Bernhard Schölkopf, Carl Allen
A Probabilistic Model to explain Self-Supervised Representation Learning. CoRR (2024)
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 (2024)
Jonathan Thomm, Aleksandar Terzic, Geethan Karunaratne, Giacomo Camposampiero, Bernhard Schölkopf, Abbas Rahimi
Limits of Transformer Language Models on Algorithmic Learning. CoRR (2024)
Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. CoRR (2024)
Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Häufle, Bernhard Schölkopf, Dieter Büchler
Identifying Policy Gradient Subspaces. CoRR (2024)
Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? CoRR (2024)
Partha Ghosh, Soubhik Sanyal, Cordelia Schmid, Bernhard Schölkopf
RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks. CoRR (2024)
Alexander Song, Sai Nikhilesh Murty Kottapalli, Rahul Goyal, Bernhard Schölkopf, Peer Fischer
Low-power scalable multilayer optoelectronic neural networks enabled with incoherent light. CoRR (2024)
Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models. CoRR (2024)
Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina
The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks. CoRR (2023)
Fernando Gonzalez, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. CoRR (2023)
Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rätsch, Bernhard Schölkopf
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. ICML (2023)
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
Bridging the Gap to Real-World Object-Centric Learning. ICLR (2023)
Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Ryan Cotterell
All Roads Lead to Rome? Exploring the Invariance of Transformers' Representations. CoRR (2023)
Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica Pogancic, Julius von Kügelgen, Bernhard Schölkopf
Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features. NeurIPS (2023)
Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
Causal effect estimation from observational and interventional data through matrix weighted linear estimators. UAI (2023)
Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi
Robustness Implies Fairness in Causal Algorithmic Recourse. FAccT (2023)
Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf
Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling. CoRR (2023)
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)
Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf
On the Interventional Kullback-Leibler Divergence. CLeaR (2023)
Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick
Membership Inference Attacks against Language Models via Neighbourhood Comparison. ACL (Findings) (2023)
Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rätsch, Bernhard Schölkopf
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. CoRR (2023)
Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf
Learning Locomotion Skills from MPC in Sensor Space. L4DC (2023)
Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. ICLR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. CoRR (2023)
David F. Jenny, Yann Billeter, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin
Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures. CoRR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. NeurIPS (2023)
Jan Schneider, Pierre Schumacher, Daniel F. B. Häufle, Bernhard Schölkopf, Dieter Büchler
Investigating the Impact of Action Representations in Policy Gradient Algorithms. CoRR (2023)
Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. ACL (1) (2023)
Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato
normflows: A PyTorch Package for Normalizing Flows. CoRR (2023)
Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf
Pairwise Similarity Learning is SimPLE. ICCV (2023)
Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey
Metrizing Weak Convergence with Maximum Mean Discrepancies. J. Mach. Learn. Res. 24 (2023)
Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence
Dataflow graphs as complete causal graphs. CAIN (2023)
Laurence I. Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
SE(3) Equivariant Augmented Coupling Flows. CoRR (2023)
Wendong Liang, Armin Kekic, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
Causal Component Analysis. NeurIPS (2023)
Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf
Structure by Architecture: Structured Representations without Regularization. ICLR (2023)
Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
The passive symmetries of machine learning. CoRR (2023)
Fernando Gonzalez Adauto, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. EMNLP (Findings) (2023)
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 (2023)
Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
Provably Learning Object-Centric Representations. CoRR (2023)
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 Pohang, 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 (2023)
Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F. Grewe, Bernhard Schölkopf
Homomorphism AutoEncoder - Learning Group Structured Representations from Observed Transitions. ICML (2023)
Timothy D. Gebhard, Daniel Angerhausen, Björn S. Konrad, Eleonora Alei, Sascha P. Quanz, Bernhard Schölkopf
Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks. CoRR (2023)
Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszar
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. NeurIPS (2023)
Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. IROS (2023)
Julius von Kügelgen, Michel Besserve, Wendong Liang, Luigi Gresele, Armin Kekic, Elias Bareinboim, David M. Blei, Bernhard Schölkopf
Nonparametric Identifiability of Causal Representations from Unknown Interventions. NeurIPS (2023)
Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence
Dataflow graphs as complete causal graphs. CoRR (2023)
Felix Laumann, Julius von Kügelgen, Junhyung Park, Bernhard Schölkopf, Mauricio Barahona
Kernel-Based Independence Tests for Causal Structure Learning on Functional Data. Entropy 25 (12) (2023)
Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CLeaR (2023)
Simon Guist, Jan Schneider, Alexander Dittrich, Vincent Berenz, Bernhard Schölkopf, Dieter Büchler
Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning. CoRR (2023)
Simon Guist, Jan Schneider, Vincent Berenz, Alexander Dittrich, Bernhard Schölkopf, Dieter Büchler
Hindsight States: Blending Sim & Real Task Elements for Efficient Reinforcement Learning. Robotics: Science and Systems (2023)
Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS (2023)
Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. CoRR (2023)
Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica, Julius von Kügelgen, Bernhard Schölkopf
Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features. CoRR (2023)
Siyuan Guo, Jonas Wildberger, Bernhard Schölkopf
Out-of-Variable Generalization. CoRR (2023)
Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, Isabel Valera
A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations. ACM Comput. Surv. 55 (5) (2023)
Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. CoRR (2023)
Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
On the Identifiability and Estimation of Causal Location-Scale Noise Models. ICML (2023)
Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. CoRR (2023)
Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf
Controlling Text-to-Image Diffusion by Orthogonal Finetuning. CoRR (2023)
Yiwen Ding, Jiarui Liu, Zhiheng Lyu, Kun Zhang, Bernhard Schölkopf, Zhijing Jin, Rada Mihalcea
Voices of Her: Analyzing Gender Differences in the AI Publication World. CoRR (2023)
Max-Olivier Van Bastelaer, Heiner Kremer, Valentin Volchkov, Jean-Claude Passy, Bernhard Schölkopf
Glare Removal for Astronomical Images with High Local Dynamic Range. ICCP (2023)
Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
Provably Learning Object-Centric Representations. ICML (2023)
Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf
Pairwise Similarity Learning is SimPLE. CoRR (2023)
Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
A Measure-Theoretic Axiomatisation of Causality. NeurIPS (2023)
Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. NeurIPS (2023)
Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel
Jacobian-based Causal Discovery with Nonlinear ICA. Trans. Mach. Learn. Res. 2023 (2023)
Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf
Can Large Language Models Infer Causation from Correlation? CoRR (2023)
Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato
Flow Annealed Importance Sampling Bootstrap. ICLR (2023)
Simon Guist, Jan Schneider, Hao Ma, Vincent Berenz, Julian Martus, Felix Grüninger, Michael Mühlebach, Jonathan Fiene, Bernhard Schölkopf, Dieter Büchler
A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions. CoRR (2023)
Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Negar Kiyavash, Mrinmaya Sachan, Bernhard Schölkopf
CausalCite: A Causal Formulation of Paper Citations. CoRR (2023)
Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf
Ghost on the Shell: An Expressive Representation of General 3D Shapes. CoRR (2023)
Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schölkopf
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs. CoRR (2023)
Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
Estimation Beyond Data Reweighting: Kernel Method of Moments. CoRR (2023)
Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. ICLR (2023)
Armin Kekic, Bernhard Schölkopf, Michel Besserve
Targeted Reduction of Causal Models. CoRR (2023)
Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CoRR (2023)
Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato
normflows: A PyTorch Package for Normalizing Flows. J. Open Source Softw. 8 (87) (2023)
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)
Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi
Robustness Implies Fairness in Causal Algorithmic Recourse. CoRR (2023)
Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
Estimation Beyond Data Reweighting: Kernel Method of Moments. ICML (2023)
Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
Discrete Key-Value Bottleneck. ICML (2023)
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
Unsupervised Object Learning via Common Fate. CLeaR (2023)
Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf
On Data Manifolds Entailed by Structural Causal Models. ICML (2023)
Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. CoRR (2023)
Lars Lorch, Andreas Krause, Bernhard Schölkopf
Causal Modeling with Stationary Diffusions. CoRR (2023)
Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf
The Hessian perspective into the Nature of Convolutional Neural Networks. ICML (2023)
Laurence I. Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
SE(3) Equivariant Augmented Coupling Flows. NeurIPS (2023)
Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
Deep Backtracking Counterfactuals for Causally Compliant Explanations. CoRR (2023)
Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
On the Relationship Between Explanation and Prediction: A Causal View. ICML (2023)
Alexander Dittrich, Jan Schneider, Simon Guist, Nico Gürtler, Heiko Ott, Thomas Steinbrenner, Bernhard Schölkopf, Dieter Büchler
AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation. ICRA (2023)
Julius von Kügelgen, Michel Besserve, Wendong Liang, Luigi Gresele, Armin Kekic, Elias Bareinboim, David M. Blei, Bernhard Schölkopf
Nonparametric Identifiability of Causal Representations from Unknown Interventions. CoRR (2023)
Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. CoRR (2023)
Zhiheng Lyu, Zhijing Jin, Justus Mattern, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf
Psychologically-Inspired Causal Prompts. CoRR (2023)
Vincent Berenz, Felix Widmaier, Simon Guist, Bernhard Schölkopf, Dieter Büchler
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80. CoRR (2023)
Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
Reinforcement learning with model-based feedforward inputs for robotic table tennis. Auton. Robots 47 (8) (2023)
Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
A Measure-Theoretic Axiomatisation of Causality. CoRR (2023)
Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick
Membership Inference Attacks against Language Models via Neighbourhood Comparison. CoRR (2023)
Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators. CoRR (2023)
Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. NeurIPS (2023)

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Publication Activity (10 Years)

Top Topics

Top Venues

Bernhard Schölkopf