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ORCIDMaurice Weiler
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2020 – today
- 2024
[c10]Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré:
Clifford-Steerable Convolutional Neural Networks. ICML 2024- [i15]Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré:
Clifford-Steerable Convolutional Neural Networks. CoRR abs/2402.14730 (2024) - 2023
- [i14]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:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i13]Andrii Skliar, Maurice Weiler:
Hyperbolic Convolutional Neural Networks. CoRR abs/2308.15639 (2023) - 2022
- [c9]Gabriele Cesa, Leon Lang, Maurice Weiler:
A Program to Build E(N)-Equivariant Steerable CNNs. ICLR 2022 - [c8]Erik Jenner, Maurice Weiler:
Steerable Partial Differential Operators for Equivariant Neural Networks. ICLR 2022 - 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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