Frederik Träuble

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Francesco LocatelloAssistant Professor, ISTAVerified email at ista.ac.at
Stefan BauerHelmholtz | TUM | CIFARVerified email at tum.de
Andrea DittadiHelmholtz AI Munich | TUMVerified email at tum.de
Manuel WüthrichHarvard UniversityVerified email at seas.harvard.edu
Peter GehlerTübingen AI Center, University TübingenVerified email at uni-tuebingen.de
Anirudh GoyalGoogle DeepMind, Mila, Université de MontréalVerified email at umontreal.ca
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Ole WintherBiology, Univ of Copenhagen, Genomic Medicine, Rigshospitalet and Technical University of DenmarkVerified email at bio.ku.dk
Julius von KügelgenETH ZürichVerified email at stat.math.ethz.ch
Olivier BachemResearch Scientist, Google BrainVerified email at google.com
Hartmut ZohmMax-Planck-Institut für PlasmaphysikVerified email at ipp.mpg.de
Alexander NeitzMax Planck Institute for Intelligent SystemVerified email at tuebingen.mpg.de
Elliot CreagerUniversity of WaterlooVerified email at uwaterloo.ca
Niki KilbertusTechnical University of Munich & Helmholtz MunichVerified email at tum.de
Nasim RahamanMila, Montréal & Max-Planck Institute for Intelligent Systems TübingenVerified email at tuebingen.mpg.de
Michael MozerGoogle DeepMind; University of ColoradoVerified email at colorado.edu
Matthias BethgeTübingen University & Maddox Co-FounderVerified email at bethgelab.org
Chris RussellAssociate Professor, University of OxfordVerified email at oii.ox.ac.uk
Kenji KawaguchiPresidential Young Professor, National University of SingaporeVerified email at nus.edu.sg

Frederik Träuble

Max Planck Institute for Intelligent Systems

Verified email at tuebingen.mpg.de

Machine Learning


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Causalworld: A robotic manipulation benchmark for causal structure and transfer learning O Ahmed, F Träuble, A Goyal, A Neitz, Y Bengio, B Schölkopf, ... International Conference on Learning Representations 2021, 2020	150	2020
On Disentangled Representations Learned From Correlated Data F Träuble, E Creager, N Kilbertus, F Locatello, A Dittadi, A Goyal, ... International Conference on Machine Learning (ICML 2021), 2020	139	2020
On the Transfer of Disentangled Representations in Realistic Settings A Dittadi, F Träuble, F Locatello, M Wüthrich, V Agrawal, O Winther, ... International Conference on Learning Representations 2021, 2020	94	2020
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain L Schott, J von Kügelgen, F Träuble, P Gehler, C Russell, M Bethge, ... International Conference on Learning Representations 2022, 2021	79	2021
A stepladder approach to a tokamak fusion power plant H Zohm, F Träuble, W Biel, E Fable, R Kemp, H Lux, M Siccinio, ... Nuclear fusion 57 (8), 086002, 2017	74	2017
Discrete Key-Value Bottleneck F Träuble, A Goyal, N Rahaman, M Mozer, K Kawaguchi, Y Bengio, ... Fortieth International Conference on Machine Learning (ICML 2023), 2022	30	2022
The Role of Pretrained Representations for the OOD Generalization of RL Agents F Träuble, A Dittadi, M Wuthrich, F Widmaier, PV Gehler, O Winther, ... International Conference on Learning Representations 2022, 2021	24*	2021
Compositional Multi-Object Reinforcement Learning with Linear Relation Networks D Mambelli, F Träuble, S Bauer, B Schölkopf, F Locatello arXiv preprint arXiv:2201.13388, 2022	21	2022
Backward-Compatible Prediction Updates: A Probabilistic Approach F Träuble, J von Kügelgen, M Kleindessner, F Locatello, B Schölkopf, ... Advances in Neural Information Processing Systems 34, 2021	20	2021
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability C Eastwood, AL Nicolicioiu, J von Kügelgen, A Kekić, F Träuble, A Dittadi, ... International Conference on Learning Representations 2023, 2022	19	2022
An improved equation of state for air plasma simulations F Träuble, ST Millmore, N Nikiforakis Physics of Fluids 33 (3), 2021	18	2021
Representation Learning for Out-of-distribution Generalization in Reinforcement Learning F Träuble, A Dittadi, M Wuthrich, F Widmaier, PV Gehler, O Winther, ... ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021	9*	2021
Unlearning via Sparse Representations V Shah, F Träuble, A Malik, H Larochelle, M Mozer, S Arora, Y Bengio, ... arXiv preprint arXiv:2311.15268, 2023	8	2023
Where to locate DEMO in a one-step-to-an-FPP strategy H Zohm, FJ Träuble, W Biel, E Fable, R Kemp, R Wenninger 43rd EPS Conference on Plasma Physics, 2016	8	2016
A General Purpose Neural Architecture for Geospatial Systems N Rahaman, M Weiss, F Träuble, F Locatello, A Lacoste, Y Bengio, C Pal, ... AI + HADR Workshop at 36th Conference on Neural Information Processing Systems, 2022	4	2022
On the DCI Framework for Evaluating Disentangled Representations: Extensions and Connections to Identifiability C Eastwood, AL Nicolicioiu, J Von Kügelgen, A Kekic, F Träuble, A Dittadi, ... UAI 2022 Workshop on Causal Representation Learning, 2022	2	2022
Boxhead: A Dataset for Learning Hierarchical Representations Y Chen, F Träuble, A Dittadi, S Bauer, B Schölkopf NeurIPS 2021 Workshop on Shared Visual Representations in Human and Machine …, 2021	2	2021
Multi-megabase scale genome interpretation with genetic language models F Träuble, L Stuart, A Georgiou, P Notin, A Mehrjou, R Schwessinger, ... arXiv preprint arXiv:2501.07737, 2025		2025
Representation Learning for Out-of-distribution Generalization in Reinforcement Learning Learning F Träuble, A Dittadi, M Wüthrich, F Widmaier, P Gehler, O Winther, ... ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021), 2021		2021
DCI-ES: AN EXTENDED DISENTANGLEMENT FRAME C Eastwood, AL Nicolicioiu, J von Kügelgen, A Kekic, F Träuble, A Dittadi, ...

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