Simon Buchholz

31 papers A* 12A 2Misc 1Journal 15Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Logit Distance Bounds Representational Similarity.
CoRR
Beatrix M. G. Nielsen, Emanuele Marconato, Luigi Gresele, Andrea Dittadi, Simon Buchholz
2025 — conf
Algorithmic causal structure emerging through compression.
CLeaR
Wendong Liang, Simon Buchholz, Bernhard Schölkopf
2025 J jnl
Algorithmic causal structure emerging through compression.
CoRR
Wendong Liang, Simon Buchholz, Bernhard Schölkopf
2025 J jnl
Generation is Required for Data-Efficient Perception.
CoRR
Jack Brady, Bernhard Schölkopf, Thomas Kipf, Simon Buchholz, Wieland Brendel
2025 A* conf
Interaction Asymmetry: A General Principle for Learning Composable Abstractions.
ICLR
Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel
2025 J jnl
Multi-Armed Bandits and Quantum Channel Oracles.
Quantum
Simon Buchholz, Jonas M. Kübler, Bernhard Schölkopf
2025 J jnl
Reparameterized LLM Training via Orthogonal Equivalence Transformation.
CoRR
Zeju Qiu, Simon Buchholz, Tim Z. Xiao, Maximilian Dax, Bernhard Schölkopf, Weiyang Liu
2025 J jnl
Robustness of Nonlinear Representation Learning.
CoRR
Simon Buchholz, Bernhard Schölkopf
2024 A* conf
From Causal to Concept-Based Representation Learning.
NeurIPS
Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2024 J jnl
Interaction Asymmetry: A General Principle for Learning Composable Abstractions.
CoRR
Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel
2024 J jnl
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models.
CoRR
Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2024 A* conf
Learning Partitions from Context.
NeurIPS
Simon Buchholz
2024 A conf
Products, Abstractions and Inclusions of Causal Spaces.
UAI
Simon Buchholz, Junhyung Park, Bernhard Schölkopf
2024 A* conf
Robustness of Nonlinear Representation Learning.
ICML
Simon Buchholz, Bernhard Schölkopf
2023 A* conf
A Measure-Theoretic Axiomatisation of Causality.
NeurIPS
Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
2023 J jnl
A Measure-Theoretic Axiomatisation of Causality.
CoRR
Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
2023 A* conf
Causal Component Analysis.
NeurIPS
Wendong Liang, Armin Kekic, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
2023 J jnl
Causal Component Analysis.
CoRR
Wendong Liang, Armin Kekic, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
2023 A* conf
Flow Matching for Scalable Simulation-Based Inference.
NeurIPS
Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf
2023 J jnl
Flow Matching for Scalable Simulation-Based Inference.
CoRR
Maximilian Dax, Jonas Wildberger, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf
2023 A* conf
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing.
NeurIPS
Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2023 J jnl
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing.
CoRR
Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2023 J jnl
Some Remarks on Identifiability of Independent Component Analysis in Restricted Function Classes.
Trans. Mach. Learn. Res.
Simon Buchholz
2022 A* conf
AutoML Two-Sample Test.
NeurIPS
Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf
2022 J jnl
AutoML Two-Sample Test.
CoRR
Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf
2022 A* conf
Function Classes for Identifiable Nonlinear Independent Component Analysis.
NeurIPS
Simon Buchholz, Michel Besserve, Bernhard Schölkopf
2022 J jnl
Function Classes for Identifiable Nonlinear Independent Component Analysis.
CoRR
Simon Buchholz, Michel Besserve, Bernhard Schölkopf
2022 A* conf
Kernel interpolation in Sobolev spaces is not consistent in low dimensions.
COLT
Simon Buchholz
2021 A* conf
The Inductive Bias of Quantum Kernels.
NeurIPS
Jonas M. Kübler, Simon Buchholz, Bernhard Schölkopf
2020 Misc conf
Using application knowledge to reduce cold starts in FaaS services.
SAC
David Bermbach, Ahmet-Serdar Karakaya, Simon Buchholz
2017 A conf
Trustless Intermediation in Blockchain-Based Decentralized Service Marketplaces.
ICSOC
Markus Klems, Jacob Eberhardt, Stefan Tai, Steffen Härtlein, Simon Buchholz, Ahmed Tidjani