Buchholz, Simon

21 publications

CLeaR 2025 Algorithmic Causal Structure Emerging Through Compression Liang Wendong, Simon Buchholz, Bernhard Schölkopf

ICLR 2025 Interaction Asymmetry: A General Principle for Learning Composable Abstractions Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel

NeurIPS 2025 Reparameterized LLM Training via Orthogonal Equivalence Transformation Zeju Qiu, Simon Buchholz, Tim Z. Xiao, Maximilian Dax, Bernhard Schölkopf, Weiyang Liu

NeurIPS 2024 From Causal to Concept-Based Representation Learning Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

NeurIPSW 2024 From Causal to Concept-Based Representation Learning Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Kumar Ravikumar

NeurIPSW 2024 Interaction Asymmetry: A General Principle for Learning Composable Abstractions Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Wieland Brendel

NeurIPS 2024 Learning Partitions from Context Simon Buchholz

UAI 2024 Products, Abstractions and Inclusions of Causal Spaces Simon Buchholz, Junhyung Park, Bernhard Schölkopf

ICML 2024 Robustness of Nonlinear Representation Learning Simon Buchholz, Bernhard Schölkopf

NeurIPSW 2024 Towards Object-Centric Learning with General Purpose Architectures Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel

NeurIPS 2023 A Measure-Theoretic Axiomatisation of Causality Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet

NeurIPS 2023 Causal Component Analysis Liang Wendong, Armin Kekić, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf

NeurIPS 2023 Flow Matching for Scalable Simulation-Based Inference Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen Green, Jakob H Macke, Bernhard Schölkopf

ICMLW 2023 Flow Matching for Scalable Simulation-Based Inference Jonas Bernhard Wildberger, Maximilian Dax, Simon Buchholz, Stephen R Green, Jakob H. Macke, Bernhard Schölkopf

NeurIPS 2023 Learning Linear Causal Representations from Interventions Under General Nonlinear Mixing Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep K. Ravikumar

ICMLW 2023 Learning Linear Causal Representations from Interventions Under General Nonlinear Mixing Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Kumar Ravikumar

TMLR 2023 Some Remarks on Identifiability of Independent Component Analysis in Restricted Function Classes Simon Buchholz

NeurIPS 2022 AutoML Two-Sample Test Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf

NeurIPS 2022 Function Classes for Identifiable Nonlinear Independent Component Analysis Simon Buchholz, Michel Besserve, Bernhard Schölkopf

COLT 2022 Kernel Interpolation in Sobolev Spaces Is Not Consistent in Low Dimensions Simon Buchholz

NeurIPS 2021 The Inductive Bias of Quantum Kernels Jonas Kübler, Simon Buchholz, Bernhard Schölkopf