Patrik Reizinger

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Wieland BrendelFellow at ELLIS Institut Tübingen, Group Leader, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Ferenc HuszárUniversity of CambridgeVerified email at cam.ac.uk
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Marton SzemenyeiAssistant Professor, Budapest University of Technology and EconomicsVerified email at iit.bme.hu
Matthias BethgeTübingen University & Maddox Co-FounderVerified email at bethgelab.org
Yash SharmaUniversity of Tübingen, Max Planck Institute for Intelligent SystemsVerified email at bethgelab.org
Julius von KügelgenETH ZürichVerified email at stat.math.ethz.ch
Georg MartiusUniversity of Tübingen and Max Planck Institute for Intelligent SystemsVerified email at uni-tuebingen.de
Luigi GreseleUniversity of CopenhagenVerified email at math.ku.dk
Michel BesserveMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Dominik ZietlowELLIS Institute TübingenVerified email at tue.ellis.eu
Jack BradyPhD StudentVerified email at tuebingen.mpg.de
Evgenia RusakM.Sc.Verified email at uni-tuebingen.de
Oliver BringmannProfessor of Embedded Systems, Eberhard Karls Universität Tübingen, GermanyVerified email at uni-tuebingen.de
Anna KerekesETHVerified email at ethz.ch
Szilvia UjváryPhD candidate, University of CambridgeVerified email at cam.ac.uk
Roland Simon ZimmermannUniversity of TübingenVerified email at uni-tuebingen.de
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Goutham RajendranMeta GenAIVerified email at uchicago.edu
Bálint Gyires-TóthBudapest University of Technology and EconomicsVerified email at tmit.bme.hu

Patrik Reizinger

Max Planck Institute for Intelligent Systems

Verified email at tuebingen.mpg.de - Homepage

Causal Representation Learning Independent Component Analysis Machine Learning Causal Inference


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Attention-based curiosity-driven exploration in deep reinforcement learning P Reizinger, M Szemenyei ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020	27	2020
Embrace the gap: VAEs perform independent mechanism analysis P Reizinger, L Gresele, J Brady, J Von Kügelgen, D Zietlow, B Schölkopf, ... Advances in Neural Information Processing Systems 35, 12040-12057, 2022	20	2022
Jacobian-based causal discovery with nonlinear ICA P Reizinger, Y Sharma, M Bethge, B Schölkopf, F Huszár, W Brendel Transactions on Machine Learning Research, 2023	13	2023
Attention-based curiosity in multi-agent reinforcement learning environments M Szemenyei, P Reizinger 2019 International Conference on Control, Artificial Intelligence, Robotics …, 2019	11	2019
An interventional perspective on identifiability in gaussian lti systems with independent component analysis G Rajendran, P Reizinger, W Brendel, PK Ravikumar Causal Learning and Reasoning, 41-70, 2024	3	2024
CubeSat attitude determination with decomposed Kalman filters R Patrik, V Ferenc Journal of the Brazilian Society of Mechanical Sciences and Engineering 45 …, 2023	2	2023
Content suppresses style: dimensionality collapse in contrastive learning E Rusak, P Reizinger, RS Zimmermann, O Bringmann, W Brendel NeurIPS 2022 Workshop: Self-Supervised Learning-Theory and Practice 3, 2022	2	2022
Stochastic weight matrix-based regularization methods for deep neural networks P Reizinger, B Gyires-Tóth Machine Learning, Optimization, and Data Science: 5th International …, 2019	2	2019
Independent Mechanism Analysis in GPLVMs P Reizinger, HB Li, A Ravuri, F Huszár, ND Lawrence Fifth Symposium on Advances in Approximate Bayesian Inference, 2023	1	2023
Samba: Regularized autoencoders perform sharpness-aware minimization P Reizinger, F Huszár Fifth Symposium on Advances in Approximate Bayesian Inference, 2023	1	2023
Position: Understanding LLMs Requires More Than Statistical Generalization P Reizinger, S Ujváry, A Mészáros, A Kerekes, W Brendel, F Huszár Forty-first International Conference on Machine Learning, 0	1*
Multivariable Causal Discovery with General Nonlinear Relationships P Reizinger, Y Sharma, M Bethge, B Schölkopf, F Huszár, W Brendel UAI 2022 Workshop on Causal Representation Learning, 0	1
InfoNCE: Identifying the Gap Between Theory and Practice E Rusak, P Reizinger, A Juhos, O Bringmann, RS Zimmermann, ... arXiv preprint arXiv:2407.00143, 2024		2024
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning P Reizinger, S Guo, F Huszár, B Schölkopf, W Brendel arXiv preprint arXiv:2406.14302, 2024		2024
The Falsificationist View of Machine Learning. P Reizinger Information Society/Információs Társadalom (InfTars) 23 (2), 2023		2023
Handling realistic noise in multi-agent systems with self-supervised learning and curiosity M Szemenyei, P Reizinger Journal of Artificial Intelligence and Soft Computing Research 12 (2), 135-148, 2021		2021
Learning to Play Robot Soccer from Partial Observations M Szemenyei, P Reizinger 2020 23rd International Symposium on Measurement and Control in Robotics …, 2020		2020
Kisműholdak fejlesztése a sokoldalúság és a könnyű reprodukálhatóság tükrében H Péter, R Patrik, M Dorottya, S Alexandra Repüléstudományi Közlemények 32 (2), 81–95-81–95, 2020		2020
Concept of a mobile, cameraless VR-controller framework for working environments P Reizinger, F Vajda		2018
InfoNCE: Identifying the Gap Between Theory and Practice E Rusak, P Reizinger, A Juhos, O Bringmann, RS Zimmermann, ... High-dimensional Learning Dynamics 2024: The Emergence of Structure and …, 0

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