Machine Learning Summer School 2020

Poster presentation

Slides for this presentation

Papers mentioned in this talk

  • Steerable CNNs. Cohen, T. S., & Welling, M. (2016). arXiv
  • Spherical CNNs. Cohen, T. S., Geiger, M., K√∂hler, J., & Welling, M. (2018). arXiv
  • General $E(2)$-Equivariant Steerable CNNs. Weiler, M., & Cesa, G. (2019). arXiv
  • A General Theory of Equivariant CNNs on Homogeneous Spaces. Cohen, T., Geiger, M., & Weiler, M. (2018). arXiv
  • Gauge Equivariant Convolutional Networks and the Icosahedral CNN. Cohen, T. S., Weiler, M., Kicanaoglu, B., & Welling, M. (2019). arXiv
  • Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. Finzi, M., Stanton, S., Izmailov, P., & Wilson, A. G. (2020). arXiv
  • Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds. Thomas, N., Smidt, T., Kearnes, S., Yang, L., Li, L., Kohlhoff, K., & Riley, P. (2018). arXiv
  • SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. Fuchs, F. B., Worrall, D. E., Fischer, V., & Welling, M. (2020). arXiv
  • Attentive Group Equivariant Convolutional Networks. Romero, D. W., Bekkers, E. J., Tomczak, J. M., & Hoogendoorn, M. (2020). arXiv