Nonlinear Representation Theory of Equivariant CNNs on Homogeneous Spaces Using Group Morphology

Author:

Angulo-Lopez Jesús

Publisher

Springer Nature Switzerland

Reference25 articles.

1. Lecture Notes in Computer Science;J Angulo,2021

2. Balogh, Z.M., Calogero, A., Pini, R.: The Hopf-Lax formula in Carnot groups: a control theoretic approach. Calc. Var. 49, 1379–1414 (2014)

3. Banon, G.J.F., Barrera, J.: Minimal representations for translation-invariant set mappings by mathematical morphology. SIAM J. Appl. Math. 51(6), 1782–1798 (1991)

4. Cohen, T.S., Welling, M.: Group equivariant convolutional networks. In: International of Conference on Machine Learning, pp. 2990–2999 (2016)

5. Cohen, T.S., Geiger, M., Weiler, M.: A general theory of equivariant CNNs on homogeneous spaces. In: Advances in Neural Information Processing Systems, vol. 32 (2019)

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