Causal confusion in imitation learning P De Haan, D Jayaraman, S Levine
NeurIPS 2019, 2019
298 2019 Explorations in Homeomorphic Variational Auto-Encoding L Falorsi, P de Haan, TR Davidson, N De Cao, M Weiler, P Forré, ...
ICML 2018 workshop on Theoretical Foundations and Applications of Deep …, 2018
112 2018 Gauge equivariant mesh cnns: Anisotropic convolutions on geometric graphs P De Haan, M Weiler, T Cohen, M Welling
ICLR 2021, 2020
106 2020 Natural graph networks P de Haan, T Cohen, M Welling
NeurIPS 2020, 2020
85 2020 Weakly supervised causal representation learning J Brehmer*, P De Haan*, P Lippe, T Cohen
NeurIPS 2022, 2022
81 2022 Reparameterizing Distributions on Lie Groups L Falorsi, P de Haan, TR Davidson, P Forré
AISTATS 2019, 2019
79 2019 Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows P de Haan, C Rainone, M Cheng, R Bondesan
NeurIPS 2021 workshop on Machine Learning for Physical Systems, 2021
20 2021 Mesh convolutional neural networks for wall shear stress estimation in 3D artery models J Suk, P Haan, P Lippe, C Brune, JM Wolterink
International Workshop on Statistical Atlases and Computational Models of …, 2021
19 2021 Covariance in physics and convolutional neural networks MCN Cheng, V Anagiannis, M Weiler, P de Haan, TS Cohen, M Welling
arXiv preprint arXiv:1906.02481, 2019
16 2019 Geometric Algebra Transformers J Brehmer, P De Haan, S Behrends, T Cohen
NeurIPS 2023, 2023
13 2023 Rigid body flows for sampling molecular crystal structures J Köhler, M Invernizzi, P de Haan, F Noé
ICML 2023, 2023
11 2023 Learning Lattice Quantum Field Theories with Equivariant Continuous Flows M Gerdes, P de Haan, C Rainone, R Bondesan, MCN Cheng
SciPost Physics, 2023
10 * 2023 EDGI: Equivariant Diffusion for Planning with Embodied Agents J Brehmer, J Bose, P De Haan, T Cohen
NeurIPS 2023, 2023
10 2023 Mesh neural networks for SE (3)-equivariant hemodynamics estimation on the artery wall J Suk, P de Haan, P Lippe, C Brune, JM Wolterink
Computers in Biology and Medicine, 108328, 2024
8 2024 Topological Constraints on Homeomorphic Auto-Encoding P de Haan, L Falorsi
NeurIPS 2018 Workshop on Integration of Deep Learning Theories, 2018
8 2018 Equivariant graph neural networks as surrogate for computational fluid dynamics in 3D artery models J Suk, P de Haan, P Lippe, C Brune, JM Wolterink
Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021), 2021
6 2021 Deconfounded imitation learning R Vuorio, J Brehmer, H Ackermann, D Dijkman, T Cohen, P de Haan
arXiv preprint arXiv:2211.02667, 2022
3 2022 Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers P De Haan, T Cohen, J Brehmer
AISTATS 2024, 2023
1 2023 -equivariant hemodynamics estimation on arterial surface meshes using graph convolutional networksJ Suk, P De Haan, P Lippe, C Brune, JM Wolterink
Geometric Deep Learning in Medical Image Analysis (Extended abstracts), 2022
1 2022 Efficient machine learning message passing on point cloud data DE Pim, TS Cohen
US Patent App. 18/326,800, 2024
2024