Patrick Forré

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Max WellingDistinguished Scientist at MSR AI4Science & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
Joris M. MooijProfessor in Mathematical Statistics, Korteweg-de Vries Institute, University of Amsterdam (NL)Verified email at uva.nl
Emiel HoogeboomUniversity of AmsterdamVerified email at google.com
Marco FedericiUniversity of AmsterdamVerified email at uva.nl
Maurice WeilerUniversity of AmsterdamVerified email at uva.nl
Luca FalorsiVerified email at aiconic.com
Maximilian IlseSenior Researcher @ Microsoft ResearchVerified email at microsoft.com
Pim de HaanQualcomm AI Research, University of AmsterdamVerified email at uva.nl
Stephan BongersPh.D. Candidate, University of AmsterdamVerified email at uva.nl
Zeynep AkataProfessor at TUM and Director at Helmholtz MunichVerified email at helmholtz-munich.de
Jakub M. TomczakAssociate professor at Eindhoven University of TechnologyVerified email at tue.nl
Jonas PetersProfessor of Statistics, ETH ZurichVerified email at stat.math.ethz.ch
Rianne van den BergPrincipal Research Manager, Microsoft ResearchVerified email at microsoft.com
Frank NIELSENSony Computer Science Laboratories Inc (Sony CSL)Verified email at acm.org
Ralph WijersAnton Pannekoek Institute for Astronomy, University of AmsterdamVerified email at uva.nl
Antonia RowlinsonUniversiteit van Amsterdam & ASTRONVerified email at uva.nl

Patrick Forré

Assistant Professor Machine Learning, AI4Science Lab Manager, University of Amsterdam

Verified email at uva.nl

Causality Statistics Machine Learning Math4AI AI4Science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions E Hoogeboom, D Nielsen, P Jaini, P Forré, M Welling NeurIPS 2021, 2021	297*	2021
Learning Robust Representations via Multi-View Information Bottleneck M Federici, A Dutta, P Forré, N Kushman, Z Akata ICLR 2020, 2020	227	2020
Foundations of Structural Causal Models with Cycles and Latent Variables S Bongers, P Forré, J Peters, JM Mooij Annals of Statistics 2021 49 (5), 2885-2915, 2021	143	2021
Explorations in Homeomorphic Variational Auto-Encoding L Falorsi, P de Haan, TR Davidson, N De Cao, M Weiler, P Forré, ... ICML 2018 Workshop: Theoretical Foundations and Applications of Deep …, 2018	116	2018
Sinkhorn AutoEncoders G Patrini, R Berg, P Forré, M Carioni, S Bhargav, M Welling, T Genewein, ... UAI 2019, 2019	108	2019
Reparameterizing Distributions on Lie Groups L Falorsi, P de Haan, TR Davidson, P Forré AISTATS 2019; PMLR 89:3244-3253, 2019, 2019	80	2019
Selecting Data Augmentation for Simulating Interventions M Ilse, JM Tomczak, P Forré ICML 2021, 2021	70*	2021
Equivariant and Coordinate Independent Convolutional Networks - A Gauge Field Theory of Neural Networks M Weiler, P Forré, E Verlinde, M Welling https://maurice-weiler.gitlab.io/#cnn_book, 524, 2023	67*	2023
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders P Forré, JM Mooij UAI 2018, 2018	65	2018
Markov Properties for Graphical Models with Cycles and Latent Variables P Forré, JM Mooij arXiv preprint arXiv:1710.08775, 2017	61	2017
Pruning via Iterative Ranking of Sensitivity Statistics S Verdenius, M Stol, P Forré arXiv preprint arXiv:2006.00896, 2020	33	2020
Truncated Marginal Neural Ratio Estimation BK Miller, A Cole, P Forré, G Louppe, C Weniger NeurIPS 2021, 2021	32	2021
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias P Forré, JM Mooij UAI 2019; PMLR 115:71-80, 2020, 2019	32	2019
Neural Ordinary Differential Equations on Manifolds L Falorsi, P Forré ICML 2020 Workshop INNF+: Invertible Neural Networks, Normalizing Flows, and …, 2020	31	2020
Strongly free sequences and pro-p-groups of cohomological dimension 2. P Forré Journal für die Reine und Angewandte Mathematik 2011 (658), 2011	22	2011
Clifford Group Equivariant Neural Networks D Ruhe, J Brandstetter, P Forré NeurIPS 2023, 2023	15	2023
Contrastive Neural Ratio Estimation BK Miller, C Weniger, P Forré NeurIPS 2022, 2022	15	2022
Bayesian optimization of comprehensive two-dimensional liquid chromatography separations J Boelrijk, B Pirok, B Ensing, P Forré Journal of Chromatography A 1659, 2021	15	2021
Combining interventional and observational data using causal reductions M Ilse, P Forré, M Welling, JM Mooij arXiv preprint arXiv:2103.04786, 2021	15*	2021
An Information-theoretic Approach to Distribution Shifts M Federici, R Tomioka, P Forré NeurIPS 2021, 2021	13	2021

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