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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
1012020
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
86*2018
Sinkhorn AutoEncoders
G Patrini, R Berg, P Forré, M Carioni, S Bhargav, M Welling, T Genewein, ...
UAI 2019, 2019
692019
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
E Hoogeboom, D Nielsen, P Jaini, P Forré, M Welling
NeurIPS 2021, 2021
65*2021
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
61*2021
Reparameterizing Distributions on Lie Groups
L Falorsi, P de Haan, TR Davidson, P Forré
AISTATS 2019; PMLR 89:3244-3253, 2019, 2019
572019
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders
P Forré, JM Mooij
UAI 2018, 2018
432018
Markov Properties for Graphical Models with Cycles and Latent Variables
P Forré, JM Mooij
arXiv preprint arXiv:1710.08775, 2017
432017
Selecting Data Augmentation for Simulating Interventions
M Ilse, JM Tomczak, P Forré
ICML 2021, 2021
342021
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
282021
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias
P Forré, JM Mooij
UAI 2019; PMLR 115:71-80, 2020, 2019
25*2019
Strongly free sequences and pro-p-groups of cohomological dimension 2.
P Forré
Journal für die Reine und Angewandte Mathematik 2011 (658), 2011
19*2011
Neural Ordinary Differential Equations on Manifolds
L Falorsi, P Forré
ICML 2020 Workshop INNF+: Invertible Neural Networks, Normalizing Flows, and …, 2020
162020
Pruning via Iterative Ranking of Sensitivity Statistics
S Verdenius, M Stol, P Forré
arXiv preprint arXiv:2006.00896, 2020
162020
Truncated Marginal Neural Ratio Estimation
BK Miller, A Cole, P Forré, G Louppe, C Weniger
NeurIPS 2021, 2021
102021
Combining interventional and observational data using causal reductions
M Ilse, P Forré, M Welling, JM Mooij
arXiv preprint arXiv:2103.04786, 2021
7*2021
An Information-theoretic Approach to Distribution Shifts
M Federici, R Tomioka, P Forré
NeurIPS 2021, 2021
52021
Transitional Conditional Independence
P Forré
arXiv preprint arXiv:2104.11547, 2021
52021
Bayesian optimization of comprehensive two-dimensional liquid chromatography separations
J Boelrijk, B Pirok, B Ensing, P Forré
Journal of Chromatography A 1659, 2021
42021
Improving Fair Predictions Using Variational Inference In Causal Models
R Helwegen, C Louizos, P Forré
arXiv preprint arXiv:2008.10880, 2020
42020
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