Follow
Patrick Forré
Patrick Forré
Assistant Professor Machine Learning, AI4Science Lab Manager, University of Amsterdam
Verified email at uva.nl
Title
Cited by
Cited by
Year
Learning Robust Representations via Multi-View Information Bottleneck
M Federici, A Dutta, P Forré, N Kushman, Z Akata
ICLR 2020, 2020
1422020
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
E Hoogeboom, D Nielsen, P Jaini, P Forré, M Welling
NeurIPS 2021, 2021
138*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
93*2018
Sinkhorn AutoEncoders
G Patrini, R Berg, P Forré, M Carioni, S Bhargav, M Welling, T Genewein, ...
UAI 2019, 2019
872019
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
852021
Reparameterizing Distributions on Lie Groups
L Falorsi, P de Haan, TR Davidson, P Forré
AISTATS 2019; PMLR 89:3244-3253, 2019, 2019
682019
Selecting Data Augmentation for Simulating Interventions
M Ilse, JM Tomczak, P Forré
ICML 2021, 2021
472021
Markov Properties for Graphical Models with Cycles and Latent Variables
P Forré, JM Mooij
arXiv preprint arXiv:1710.08775, 2017
472017
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders
P Forré, JM Mooij
UAI 2018, 2018
462018
Coordinate Independent Convolutional Networks - Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds
M Weiler, P Forré, E Verlinde, M Welling
arXiv preprint arXiv:2106.06020, 2021
412021
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias
P Forré, JM Mooij
UAI 2019; PMLR 115:71-80, 2020, 2019
262019
Pruning via Iterative Ranking of Sensitivity Statistics
S Verdenius, M Stol, P Forré
arXiv preprint arXiv:2006.00896, 2020
212020
Neural Ordinary Differential Equations on Manifolds
L Falorsi, P Forré
ICML 2020 Workshop INNF+: Invertible Neural Networks, Normalizing Flows, and …, 2020
202020
Strongly free sequences and pro-p-groups of cohomological dimension 2.
P Forré
Journal für die Reine und Angewandte Mathematik 2011 (658), 2011
202011
Truncated Marginal Neural Ratio Estimation
BK Miller, A Cole, P Forré, G Louppe, C Weniger
NeurIPS 2021, 2021
122021
Combining interventional and observational data using causal reductions
M Ilse, P Forré, M Welling, JM Mooij
arXiv preprint arXiv:2103.04786, 2021
9*2021
An Information-theoretic Approach to Distribution Shifts
M Federici, R Tomioka, P Forré
NeurIPS 2021, 2021
72021
Bayesian optimization of comprehensive two-dimensional liquid chromatography separations
J Boelrijk, B Pirok, B Ensing, P Forré
Journal of Chromatography A 1659, 2021
62021
Self Normalizing Flows
TA Keller, JWT Peters, P Jaini, E Hoogeboom, P Forré, M Welling
ICML 2021, 2021
52021
Improving Fair Predictions Using Variational Inference In Causal Models
R Helwegen, C Louizos, P Forré
arXiv preprint arXiv:2008.10880, 2020
52020
The system can't perform the operation now. Try again later.
Articles 1–20