Forré, Patrick

38 publications

ICLRW 2025 AdS-GNN - A Conformally Equivariant Graph Neural Network Maksim Zhdanov, Nabil Iqbal, Erik J Bekkers, Patrick Forré

ICLRW 2025 Clifford Group Equivariant Diffusion Models for 3D Molecular Generation Cong Liu, Sharvaree Vadgama, David Ruhe, Erik J Bekkers, Patrick Forré

TMLR 2025 Modeling Human Beliefs About AI Behavior for Scalable Oversight Leon Lang, Patrick Forré

CLeaR 2025 Robust Multi-View Co-Expression Network Inference Teodora Pandeva, Martijs Johannes Jonker, Leendert Hamoen, Joris Mooij, Patrick Forré

ICML 2025 The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret Lukas Fluri, Leon Lang, Alessandro Abate, Patrick Forré, David Krueger, Joar Max Viktor Skalse

ICLR 2024 Clifford Group Equivariant Simplicial Message Passing Networks Cong Liu, David Ruhe, Floor Eijkelboom, Patrick Forré

ICML 2024 Clifford-Steerable Convolutional Neural Networks Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré

AISTATS 2024 Deep Anytime-Valid Hypothesis Testing Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar

TMLR 2024 E-Valuating Classifier Two-Sample Tests Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forré

UAI 2024 Early-Exit Neural Networks with Nested Prediction Sets Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric Nalisnick

ICLR 2024 Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling

ICLR 2024 Lie Group Decompositions for Equivariant Neural Networks Mircea Mironenco, Patrick Forré

ICMLW 2024 Multivector Neurons: Better and Faster O(n)-Equivariant Clifford GNNs Cong Liu, David Ruhe, Patrick Forré

NeurIPSW 2024 Robust Multi-View Co-Expression Network Inference Teodora Pandeva, Martijs Johannes Jonker, Leendert Hamoen, Joris Mooij, Patrick Forré

ICMLW 2024 SINR: Equivariant Neural Vector Fields David Ruhe, Patrick Forré

ICMLW 2024 Towards Detailed and Interpretable Hybrid Modeling of Continental-Scale Bird Migration Fiona Lippert, Bart Kranstauber, Patrick Forré, Emiel van Loon

NeurIPS 2023 Clifford Group Equivariant Neural Networks David Ruhe, Johannes Brandstetter, Patrick Forré

NeurIPS 2023 Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré

ICLR 2023 Equivariance-Aware Architectural Optimization of Neural Networks Kaitlin Maile, Dennis George Wilson, Patrick Forré

ICLR 2023 Multi-Objective Optimization via Equivariant Deep Hypervolume Approximation Jim Boelrijk, Bernd Ensing, Patrick Forré

ICLRW 2023 Multi-View Independent Component Analysis for Omics Data Integration Teodora Pandeva, Patrick Forré

UAI 2023 Multi-View Independent Component Analysis with Shared and Individual Sources Teodora Pandeva, Patrick Forré

ICMLW 2023 Simulation-Based Inference with the Generalized Kullback-Leibler Divergence Benjamin Kurt Miller, Marco Federici, Christoph Weniger, Patrick Forré

NeurIPS 2022 Contrastive Neural Ratio Estimation Benjamin K Miller, Christoph Weniger, Patrick Forré

NeurIPSW 2022 Physics-Informed Inference of Aerial Animal Movements from Weather Radar Data Fiona Lippert, Bart Kranstauber, E. Emiel van Loon, Patrick Forré

ICLR 2022 Self-Supervised Inference in State-Space Models David Ruhe, Patrick Forré

NeurIPSW 2022 Towards Architectural Optimization of Equivariant Neural Networks over Subgroups Kaitlin Maile, Dennis George Wilson, Patrick Forré

NeurIPS 2021 An Information-Theoretic Approach to Distribution Shifts Marco Federici, Ryota Tomioka, Patrick Forré

NeurIPS 2021 Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling

ICML 2021 Selecting Data Augmentation for Simulating Interventions Maximilian Ilse, Jakub M Tomczak, Patrick Forré

ICML 2021 Self Normalizing Flows Thomas A Keller, Jorn W.T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling

ICLRW 2021 Simplicial Regularization Jose Gallego-Posada, Patrick Forré

NeurIPS 2021 Truncated Marginal Neural Ratio Estimation Benjamin K Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger

ICLR 2020 Learning Robust Representations via Multi-View Information Bottleneck Marco Federici, Anjan Dutta, Patrick Forré, Nate Kushman, Zeynep Akata

UAI 2019 Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias Patrick Forré, Joris M. Mooij

AISTATS 2019 Reparameterizing Distributions on Lie Groups Luca Falorsi, Pim de Haan, Tim R. Davidson, Patrick Forré

UAI 2019 Sinkhorn AutoEncoders Giorgio Patrini, Rianne Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen

UAI 2018 Constraint-Based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders Patrick Forré, Joris M. Mooij