Maurice Weiler

According to our database, Maurice Weiler authored at least 16 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Clifford-Steerable Convolutional Neural Networks.

Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Hyperbolic Convolutional Neural Networks.

Andrii Skliar, Maurice Weiler

CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.

Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

CoRR, 2023

2022

Steerable Partial Differential Operators for Equivariant Neural Networks.

Erik Jenner, Maurice Weiler

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Program to Build E(N)-Equivariant Steerable CNNs.

Gabriele Cesa, Leon Lang, Maurice Weiler

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Coordinate Independent Convolutional Networks - Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds.

Maurice Weiler, Patrick Forré, Erik Verlinde, Max Welling

CoRR, 2021

A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels.

Leon Lang, Maurice Weiler

Proceedings of the 9th International Conference on Learning Representations, 2021

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs.

Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Covariance in Physics and Convolutional Neural Networks.

Miranda C. N. Cheng, Vassilis Anagiannis, Maurice Weiler, Pim de Haan, Taco S. Cohen, Max Welling

CoRR, 2019

General E(2)-Equivariant Steerable CNNs.

Maurice Weiler, Gabriele Cesa

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A General Theory of Equivariant CNNs on Homogeneous Spaces.

Taco S. Cohen, Mario Geiger, Maurice Weiler

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Gauge Equivariant Convolutional Networks and the Icosahedral CNN.

Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Explorations in Homeomorphic Variational Auto-Encoding.

Luca Falorsi, Pim de Haan, Tim R. Davidson, Nicola De Cao, Maurice Weiler, Patrick Forré, Taco S. Cohen

CoRR, 2018

Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks).

Taco S. Cohen, Mario Geiger, Maurice Weiler

CoRR, 2018

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.

Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Steerable Filters for Rotation Equivariant CNNs.

Maurice Weiler, Fred A. Hamprecht, Martin Storath

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018