Learning Steerable Filters for Rotation Equivariant CNNs. - Maurice Weiler; Fred A. Hamprecht; Martin Storath (CVPR, 2018)

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. - Maurice Weiler; Mario Geiger; Max Welling; Wouter Boomsma; Taco Cohen (NeurIPS, 2018)

Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks). - Taco S. Cohen; Mario Geiger; Maurice Weiler (CoRR, 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)

Gauge Equivariant Convolutional Networks and the Icosahedral CNN. - Taco Cohen; Maurice Weiler; Berkay Kicanaoglu; Max Welling (ICML, 2019)

A General Theory of Equivariant CNNs on Homogeneous Spaces. - Taco S. Cohen; Mario Geiger; Maurice Weiler (NeurIPS, 2019)

General E(2)-Equivariant Steerable CNNs. - Maurice Weiler; Gabriele Cesa (NeurIPS, 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)

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. - Pim de Haan; Maurice Weiler; Taco Cohen; Max Welling (ICLR, 2021)

A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels. - Leon Lang; Maurice Weiler (ICLR, 2021)

Coordinate Independent Convolutional Networks - Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds. - Maurice Weiler; Patrick Forré; Erik Verlinde; Max Welling (CoRR, 2021)

A Program to Build E(N)-Equivariant Steerable CNNs. - Gabriele Cesa; Leon Lang; Maurice Weiler (ICLR, 2022)

Steerable Partial Differential Operators for Equivariant Neural Networks. - Erik Jenner; Maurice Weiler (ICLR, 2022)

Hyperbolic Convolutional Neural Networks. - Andrii Skliar; Maurice Weiler (CoRR, 2023)

Clifford-Steerable Convolutional Neural Networks. - Maksim Zhdanov 001; David Ruhe; Maurice Weiler; Ana Lucic; Johannes Brandstetter; Patrick Forré (ICML, 2024)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

Equivariant non-linear maps for neural networks on homogeneous spaces. - Elias Nyholm; Oscar Carlsson; Maurice Weiler; Daniel Persson (CoRR, 2025)