Pim de Haan
Pim de Haan
Qualcomm AI Research, University of Amsterdam
Geverifieerd e-mailadres voor uva.nl - Homepage
Titel
Geciteerd door
Geciteerd door
Jaar
Causal confusion in imitation learning
P de Haan, D Jayaraman, S Levine
Advances in Neural Information Processing Systems 32, 11698-11709, 2019
812019
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
57*2018
Reparameterizing Distributions on Lie Groups
L Falorsi, P de Haan, TR Davidson, P Forré
AISTATS 2019, 2019
392019
Gauge equivariant mesh cnns: Anisotropic convolutions on geometric graphs
P De Haan, M Weiler, T Cohen, M Welling
ICLR 2021, 2020
272020
Natural graph networks
P de Haan, T Cohen, M Welling
NeurIPS 2020, 2020
102020
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
72019
Topological Constraints on Homeomorphic Auto-Encoding
P de Haan, L Falorsi
NeurIPS 2018 Workshop on Integration of Deep Learning Theories, 2018
52018
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows
P de Haan, C Rainone, M Cheng, R Bondesan
arXiv preprint arXiv:2110.02673, 2021
2021
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models
J Suk, P de Haan, P Lippe, C Brune, JM Wolterink
arXiv preprint arXiv:2109.04797, 2021
2021
Gauge equivariant geometric graph convolutional neural network
DE Pim, M Weiler, TS Cohen, M Welling
US Patent App. 17/169,338, 2021
2021
Gauge Equivariant Spherical CNNs
B Kicanaoglu, P de Haan, T Cohen
2019
Natural Graph Networks Download PDF
P de Haan, T Cohen, M Welling
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–12