Pim de Haan - RankMe

39 papers A* 9A 2Journal 27Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	BLIPs: Bayesian Learned Interatomic Potentials. CoRR Dario Coscia, Pim de Haan, Max Welling
2025	J	`jnl`	Does equivariance matter at scale? Trans. Mach. Learn. Res. Johann Brehmer, Sönke Behrends, Pim de Haan, Taco Cohen
2024	J	`jnl`	A Lorentz-Equivariant Transformer for All of the LHC. CoRR Johann Brehmer, Victor Bresó, Pim de Haan, Tilman Plehn, Huilin Qu, Jonas Spinner, Jesse Thaler
2024	J	`jnl`	Continuous normalizing flows for lattice gauge theories. CoRR Mathis Gerdes, Pim de Haan, Roberto Bondesan, Miranda C. N. Cheng
2024	J	`jnl`	Deconfounding Imitation Learning with Variational Inference. Trans. Mach. Learn. Res. Risto Vuorio, Pim de Haan, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen
2024	J	`jnl`	Does equivariance matter at scale? CoRR Johann Brehmer, Sönke Behrends, Pim de Haan, Taco Cohen
2024	A	`conf`	Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. AISTATS Pim de Haan, Taco Cohen, Johann Brehmer
2024	A*	`conf`	Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. NeurIPS Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer
2024	J	`jnl`	Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. CoRR Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer
2024	J	`jnl`	Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall. Comput. Biol. Medicine Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
2024	A*	`conf`	Noether's Razor: Learning Conserved Quantities. NeurIPS Tycho F. A. van der Ouderaa, Mark van der Wilk, Pim de Haan
2024	J	`jnl`	Noether's razor: Learning Conserved Quantities. CoRR Tycho F. A. van der Ouderaa, Mark van der Wilk, Pim de Haan
2023	A*	`conf`	EDGI: Equivariant Diffusion for Planning with Embodied Agents. NeurIPS Johann Brehmer, Joey Bose, Pim de Haan, Taco S. Cohen
2023	J	`jnl`	EDGI: Equivariant Diffusion for Planning with Embodied Agents. CoRR Johann Brehmer, Joey Bose, Pim de Haan, Taco Cohen
2023	J	`jnl`	Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. CoRR Pim de Haan, Taco Cohen, Johann Brehmer
2023	J	`jnl`	FoMo Rewards: Can we cast foundation models as reward functions? CoRR Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan, Taco Cohen
2023	A*	`conf`	Geometric Algebra Transformer. NeurIPS Johann Brehmer, Pim de Haan, Sönke Behrends, Taco S. Cohen
2023	J	`jnl`	Geometric Algebra Transformers. CoRR Johann Brehmer, Pim de Haan, Sönke Behrends, Taco Cohen
2023	A*	`conf`	Rigid Body Flows for Sampling Molecular Crystal Structures. ICML Jonas Köhler, Michele Invernizzi, Pim de Haan, Frank Noé
2023	J	`jnl`	Rigid body flows for sampling molecular crystal structures. CoRR Jonas Köhler, Michele Invernizzi, Pim de Haan, Frank Noé
2022	J	`jnl`	Deconfounded Imitation Learning. CoRR Risto Vuorio, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen, Pim de Haan
2022	J	`jnl`	Learning Lattice Quantum Field Theories with Equivariant Continuous Flows. CoRR Mathis Gerdes, Pim de Haan, Corrado Rainone, Roberto Bondesan, Miranda C. N. Cheng
2022	J	`jnl`	Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall. CoRR Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
2022	A*	`conf`	Weakly supervised causal representation learning. NeurIPS Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S. Cohen
2022	J	`jnl`	Weakly supervised causal representation learning. CoRR Johann Brehmer, Pim de Haan, Phillip Lippe, Taco Cohen
2021	A*	`conf`	Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. ICLR Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
2021	—	`conf`	Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models. STACOM@MICCAI Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
2021	J	`jnl`	Mesh convolutional neural networks for wall shear stress estimation in 3D artery models. CoRR Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
2021	J	`jnl`	Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows. CoRR Pim de Haan, Corrado Rainone, Miranda C. N. Cheng, Roberto Bondesan
2020	J	`jnl`	Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. CoRR Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
2020	A*	`conf`	Natural Graph Networks. NeurIPS Pim de Haan, Taco S. Cohen, Max Welling
2020	J	`jnl`	Natural Graph Networks. CoRR Pim de Haan, Taco Cohen, Max Welling
2019	A*	`conf`	Causal Confusion in Imitation Learning. NeurIPS Pim de Haan, Dinesh Jayaraman, Sergey Levine
2019	J	`jnl`	Causal Confusion in Imitation Learning. CoRR Pim de Haan, Dinesh Jayaraman, Sergey Levine
2019	J	`jnl`	Covariance in Physics and Convolutional Neural Networks. CoRR Miranda C. N. Cheng, Vassilis Anagiannis, Maurice Weiler, Pim de Haan, Taco S. Cohen, Max Welling
2019	A	`conf`	Reparameterizing Distributions on Lie Groups. AISTATS Luca Falorsi, Pim de Haan, Tim R. Davidson, Patrick Forré
2019	J	`jnl`	Reparameterizing Distributions on Lie Groups. CoRR Luca Falorsi, Pim de Haan, Tim R. Davidson, Patrick Forré
2018	J	`jnl`	Explorations in Homeomorphic Variational Auto-Encoding. CoRR Luca Falorsi, Pim de Haan, Tim R. Davidson, Nicola De Cao, Maurice Weiler, Patrick Forré, Taco S. Cohen
2018	J	`jnl`	Topological Constraints on Homeomorphic Auto-Encoding. CoRR Pim de Haan, Luca Falorsi