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2020 – today
- 2021
[c7]Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling:
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. ICLR 2021- [c6]Leon Lang
, Maurice Weiler:
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels. ICLR 2021 - [i12]Maurice Weiler, Patrick Forré, Erik Verlinde, Max Welling:
Coordinate Independent Convolutional Networks - Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds. CoRR abs/2106.06020 (2021) - [i11]Erik Jenner, Maurice Weiler:
Steerable Partial Differential Operators for Equivariant Neural Networks. CoRR abs/2106.10163 (2021) - 2020
- [i10]Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling:
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. CoRR abs/2003.05425 (2020) - [i9]Leon Lang, Maurice Weiler:
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels. CoRR abs/2010.10952 (2020)
2010 – 2019
- 2019
- [c5]Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling:
Gauge Equivariant Convolutional Networks and the Icosahedral CNN. ICML 2019: 1321-1330 - [c4]Taco S. Cohen, Mario Geiger, Maurice Weiler:
A General Theory of Equivariant CNNs on Homogeneous Spaces. NeurIPS 2019: 9142-9153 - [c3]Maurice Weiler, Gabriele Cesa:
General E(2)-Equivariant Steerable CNNs. NeurIPS 2019: 14334-14345 - [i8]Taco S. Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling:
Gauge Equivariant Convolutional Networks and the Icosahedral CNN. CoRR abs/1902.04615 (2019) - [i7]Miranda C. N. Cheng, Vassilis Anagiannis, Maurice Weiler, Pim de Haan, Taco S. Cohen, Max Welling:
Covariance in Physics and Convolutional Neural Networks. CoRR abs/1906.02481 (2019) - [i6]Maurice Weiler, Gabriele Cesa:
General E(2)-Equivariant Steerable CNNs. CoRR abs/1911.08251 (2019) - 2018
- [c2]Maurice Weiler, Fred A. Hamprecht, Martin Storath:
Learning Steerable Filters for Rotation Equivariant CNNs. CVPR 2018: 849-858 - [c1]Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen:
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. NeurIPS 2018: 10402-10413 - [i5]Taco S. Cohen, Mario Geiger, Maurice Weiler:
Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks). CoRR abs/1803.10743 (2018) - [i4]Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen:
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. CoRR abs/1807.02547 (2018) - [i3]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 abs/1807.04689 (2018) - [i2]Taco Cohen, Mario Geiger, Maurice Weiler:
A General Theory of Equivariant CNNs on Homogeneous Spaces. CoRR abs/1811.02017 (2018) - 2017
- [i1]Maurice Weiler, Fred A. Hamprecht, Martin Storath:
Learning Steerable Filters for Rotation Equivariant CNNs. CoRR abs/1711.07289 (2017)
Coauthor Index
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