Luigi Gresele

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Julius von KügelgenETH ZürichVerified email at stat.math.ethz.ch
Michel BesserveMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Francesco LocatelloAssistant Professor, ISTAVerified email at ista.ac.at
Wieland BrendelFellow at ELLIS Institut Tübingen, Group Leader, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Armin KekićMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Yash SharmaUniversity of Tübingen, Max Planck Institute for Intelligent SystemsVerified email at bethgelab.org
Vincent StimperIsomorphic LabsVerified email at isomorphiclabs.com
Liang WendongMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Giambattista ParascandoloOpenAIVerified email at openai.com
Antonio OrvietoELLIS Institute Tübingen, Max Planck Institute for Intelligent SystemsVerified email at tue.ellis.eu
Alexander NeitzMax Planck Institute for Intelligent SystemVerified email at tuebingen.mpg.de
Aapo HyvärinenUniversity of HelsinkiVerified email at helsinki.fi
Zhijing JinMax Planck Institute & ETH ZürichVerified email at ethz.ch
Yuen ChenUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Mrinmaya SachanAssistant Professor, ETH ZürichVerified email at inf.ethz.ch
Ojasv KamalResearch Engineer, MireloAIVerified email at mirelo.ai
Felix LeebMax Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Paul K RubensteinGoogle DeepMindVerified email at google.com
Arash MehrjouETH Zürich - Max Planck InstituteVerified email at tuebingen.mpg.de

Luigi Gresele

University of Copenhagen

Verified email at math.ku.dk - Homepage

Machine learning Causal Inference


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style J von Kügelgen, Y Sharma, L Gresele*, W Brendel, B Schölkopf, ... Advances in Neural Information Processing Systems 34, 2021	342	2021
Learning explanations that are hard to vary G Parascandolo, A Neitz, A Orvieto, L Gresele, B Schölkopf International Conference on Learning Representations (2021), 2020	201	2020
CLadder: Assessing Causal Reasoning in Language Models Z Jin, Y Chen, F Leeb, L Gresele, O Kamal, L Zhiheng, K Blin, ... Advances in Neural Information Processing Systems 36, 2023	117	2023
Independent mechanism analysis, a new concept? L Gresele, J von Kügelgen, V Stimper, B Schölkopf, M Besserve Advances in Neural Information Processing Systems 34, 2021	103	2021
The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA L Gresele, PK Rubenstein, A Mehrjou, F Locatello, B Schölkopf Uncertainty in Artificial Intelligence, 217-227, 2019	101	2019
Nonparametric Identifiability of Causal Representations from Unknown Interventions J von Kügelgen, M Besserve, W Liang, L Gresele, A Kekić, E Bareinboim, ... Advances in Neural Information Processing Systems 36, 2023	65	2023
Simpson's paradox in Covid-19 case fatality rates: a mediation analysis of age-related causal effects J von Kügelgen, L Gresele, B Schölkopf IEEE Transactions on Artificial Intelligence, 2021	52	2021
Causal component analysis L Wendong, A Kekić, J von Kügelgen, S Buchholz, M Besserve, ... Advances in Neural Information Processing Systems 36, 2024	43	2024
Modeling Shared Responses in Neuroimaging Studies through MultiView ICA H Richard, L Gresele, A Hyvärinen, B Thirion, A Gramfort, P Ablin Advances in Neural Information Processing Systems 33, 2020	33	2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning L Gresele, G Fissore, A Javaloy, B Schölkopf, A Hyvärinen Advances in Neural Information Processing Systems 33, 2020	31	2020
Causal Inference Through the Structural Causal Marginal Problem L Gresele, J Von Kügelgen, J Kübler*, E Kirschbaum, B Schölkopf, ... International Conference on Machine Learning, 7793-7824, 2022	29	2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis P Reizinger, L Gresele, J Brady*, J von Kügelgen, D Zietlow, ... Advances in Neural Information Processing Systems 35, 2022	23	2022
On maximum entropy and inference L Gresele, M Marsili Entropy 19 (12), 642, 2017	13	2017
Privacy-Preserving Causal Inference via Inverse Probability Weighting SK Lee, L Gresele, M Park, K Muandet NeurIPS 2019 Workshop on Privacy in Machine Learning (PriML 2019), 2019	11*	2019
Evaluating vaccine allocation strategies using simulation-assisted causal modelling A Kekic, J Dehning, L Gresele, J von Kügelgen, V Priesemann, ... Patterns, 2023	9	2023
Probing the Robustness of Independent Mechanism Analysis for Representation Learning J Sliwa, S Ghosh, V Stimper, L Gresele, B Schölkopf UAI 2022 Workshop on Causal Representation Learning, 2022	7	2022
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling E Marconato, S Lachapelle, S Weichwald, L Gresele 28th International Conference on Artificial Intelligence and Statistics …, 2025	3	2025
Independent Mechanism Analysis and the Manifold Hypothesis S Ghosh, L Gresele, J von Kügelgen, M Besserve, B Schölkopf NeurIPS 2023 Workshop on Causal Representation Learning, 2023	1	2023
On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective" S Ghosh, L Gresele, J von Kügelgen, M Besserve, B Schölkopf arXiv preprint arXiv:2202.06844, 2022	1	2022
What is causal about causal models and representations? FH Jørgensen, L Gresele, S Weichwald arXiv preprint arXiv:2501.19335, 2025		2025

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