Patrick Forré
Patrick Forré
Assistant Professor Machine Learning, AI4Science Lab Manager, University of Amsterdam
Dirección de correo verificada de
Citado por
Citado por
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
E Hoogeboom, D Nielsen, P Jaini, P Forré, M Welling
NeurIPS 2021, 2021
Learning Robust Representations via Multi-View Information Bottleneck
M Federici, A Dutta, P Forré, N Kushman, Z Akata
ICLR 2020, 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
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
Sinkhorn AutoEncoders
G Patrini, R Berg, P Forré, M Carioni, S Bhargav, M Welling, T Genewein, ...
UAI 2019, 2019
Reparameterizing Distributions on Lie Groups
L Falorsi, P de Haan, TR Davidson, P Forré
AISTATS 2019; PMLR 89:3244-3253, 2019, 2019
Selecting Data Augmentation for Simulating Interventions
M Ilse, JM Tomczak, P Forré
ICML 2021, 2021
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
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders
P Forré, JM Mooij
UAI 2018, 2018
Markov Properties for Graphical Models with Cycles and Latent Variables
P Forré, JM Mooij
arXiv preprint arXiv:1710.08775, 2017
Truncated Marginal Neural Ratio Estimation
BK Miller, A Cole, P Forré, G Louppe, C Weniger
NeurIPS 2021, 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
Neural Ordinary Differential Equations on Manifolds
L Falorsi, P Forré
ICML 2020 Workshop INNF+: Invertible Neural Networks, Normalizing Flows, and …, 2020
Pruning via Iterative Ranking of Sensitivity Statistics
S Verdenius, M Stol, P Forré
arXiv preprint arXiv:2006.00896, 2020
Clifford Group Equivariant Neural Networks
D Ruhe, J Brandstetter, P Forré
NeurIPS 2023, 2023
Strongly free sequences and pro-p-groups of cohomological dimension 2.
P Forré
Journal für die Reine und Angewandte Mathematik 2011 (658), 2011
Contrastive Neural Ratio Estimation
BK Miller, C Weniger, P Forré
NeurIPS 2022, 2022
Bayesian optimization of comprehensive two-dimensional liquid chromatography separations
J Boelrijk, B Pirok, B Ensing, P Forré
Journal of Chromatography A 1659, 2021
Combining interventional and observational data using causal reductions
M Ilse, P Forré, M Welling, JM Mooij
arXiv preprint arXiv:2103.04786, 2021
Chemometric Strategies for Fully Automated Interpretive Method Development in Liquid Chromatography
T Bos, J Boelrijk, S Molenaar, B van't Veer, L Niezen, D van Herwerden, ...
Analytical Chemistry 94 (46), 16060-16068, 2022
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20