Pim de Haan

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 30

Top Topics

Rotation Invariant

Imitation Learning

Top Venues

Publications

Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. CoRR (2024)
Pim de Haan, Taco Cohen, Johann Brehmer
Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. AISTATS (2024)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall. Comput. Biol. Medicine 173 (2024)
Jonas Köhler, Michele Invernizzi, Pim de Haan, Frank Noé
Rigid Body Flows for Sampling Molecular Crystal Structures. ICML (2023)
Pim de Haan, Taco Cohen, Johann Brehmer
Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. CoRR (2023)
Johann Brehmer, Joey Bose, Pim de Haan, Taco S. Cohen
EDGI: Equivariant Diffusion for Planning with Embodied Agents. NeurIPS (2023)
Johann Brehmer, Joey Bose, Pim de Haan, Taco Cohen
EDGI: Equivariant Diffusion for Planning with Embodied Agents. CoRR (2023)
Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan, Taco Cohen
FoMo Rewards: Can we cast foundation models as reward functions? CoRR (2023)
Jonas Köhler, Michele Invernizzi, Pim de Haan, Frank Noé
Rigid body flows for sampling molecular crystal structures. CoRR (2023)
Johann Brehmer, Pim de Haan, Sönke Behrends, Taco S. Cohen
Geometric Algebra Transformer. NeurIPS (2023)
Johann Brehmer, Pim de Haan, Sönke Behrends, Taco Cohen
Geometric Algebra Transformers. CoRR (2023)
Johann Brehmer, Pim de Haan, Phillip Lippe, Taco Cohen
Weakly supervised causal representation learning. CoRR (2022)
Risto Vuorio, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen, Pim de Haan
Deconfounded Imitation Learning. CoRR (2022)
Mathis Gerdes, Pim de Haan, Corrado Rainone, Roberto Bondesan, Miranda C. N. Cheng
Learning Lattice Quantum Field Theories with Equivariant Continuous Flows. CoRR (2022)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall. CoRR (2022)
Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S. Cohen
Weakly supervised causal representation learning. NeurIPS (2022)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models. STACOM@MICCAI (2021)
Pim de Haan, Corrado Rainone, Miranda C. N. Cheng, Roberto Bondesan
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows. CoRR (2021)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models. CoRR (2021)
Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. ICLR (2021)
Pim de Haan, Taco Cohen, Max Welling
Natural Graph Networks. CoRR (2020)
Pim de Haan, Taco S. Cohen, Max Welling
Natural Graph Networks. NeurIPS (2020)
Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. CoRR (2020)
Pim de Haan, Dinesh Jayaraman, Sergey Levine
Causal Confusion in Imitation Learning. NeurIPS (2019)
Luca Falorsi, Pim de Haan, Tim R. Davidson, Patrick Forré
Reparameterizing Distributions on Lie Groups. AISTATS (2019)
Pim de Haan, Dinesh Jayaraman, Sergey Levine
Causal Confusion in Imitation Learning. CoRR (2019)
Luca Falorsi, Pim de Haan, Tim R. Davidson, Patrick Forré
Reparameterizing Distributions on Lie Groups. CoRR (2019)
Miranda C. N. Cheng, Vassilis Anagiannis, Maurice Weiler, Pim de Haan, Taco S. Cohen, Max Welling
Covariance in Physics and Convolutional Neural Networks. CoRR (2019)
Pim de Haan, Luca Falorsi
Topological Constraints on Homeomorphic Auto-Encoding. CoRR (2018)
Luca Falorsi, Pim de Haan, Tim R. Davidson, Nicola De Cao, Maurice Weiler, Patrick Forré, Taco S. Cohen
Explorations in Homeomorphic Variational Auto-Encoding. CoRR (2018)