Reizinger, Patrik

18 publications

ICLR 2025 Cross-Entropy Is All You Need to Invert the Data Generating Process Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E Vogt, Randall Balestriero, Wieland Brendel, David Klindt

ICLR 2025 Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel

ICLRW 2025 Implicit Bayesian Inference Is an Insufficient Explanation of Language Model Behaviour in Compositional Tasks Szilvia Ujváry, Anna Mészáros, Wieland Brendel, Patrik Reizinger, Ferenc Huszár

AISTATS 2025 InfoNCE: Identifying the Gap Between Theory and Practice Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel

TMLR 2025 Occam’s Razor for SSL: Memory-Efficient Parametric Instance Discrimination Eric Gan, Patrik Reizinger, Alice Bizeul, Attila Juhos, Mark Ibrahim, Randall Balestriero, David Klindt, Wieland Brendel, Baharan Mirzasoleiman

ICML 2025 Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research Patrik Reizinger, Randall Balestriero, David Klindt, Wieland Brendel

CLeaR 2024 An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis Goutham Rajendran, Patrik Reizinger, Wieland Brendel, Pradeep Kumar Ravikumar

NeurIPSW 2024 DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features Attila Juhos, Alice Bizeul, Patrik Reizinger, Randall Balestriero, David Klindt, Mark Ibrahim, Julia E Vogt, Wieland Brendel

NeurIPSW 2024 DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features Attila Juhos, Alice Bizeul, Patrik Reizinger, David Klindt, Randall Balestriero, Mark Ibrahim, Julia E Vogt, Wieland Brendel

NeurIPSW 2024 Exploring a Bayesian View on Compositional and Counterfactual Generalization Patrik Reizinger, Rahul Krishnan

ICMLW 2024 InfoNCE: Identifying the Gap Between Theory and Practice Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel

ICMLW 2024 InfoNCE: Identifying the Gap Between Theory and Practice Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel

ICML 2024 Position: Understanding LLMs Requires More than Statistical Generalization Patrik Reizinger, Szilvia Ujváry, Anna Mészáros, Anna Kerekes, Wieland Brendel, Ferenc Huszár

NeurIPS 2024 Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts Anna Mészáros, Szilvia Ujváry, Wieland Brendel, Patrik Reizinger, Ferenc Huszár

NeurIPSW 2024 Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts Anna Mészáros, Szilvia Ujváry, Wieland Brendel, Patrik Reizinger, Ferenc Huszár

ICMLW 2023 Desiderata for Representation Learning from Identifiability, Disentanglement, and Group-Structuredness Hamza Keurti, Patrik Reizinger, Bernhard Schölkopf, Wieland Brendel

TMLR 2023 Jacobian-Based Causal Discovery with Nonlinear ICA Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel

NeurIPS 2022 Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve