[1] Yaser S. Abu-Mostafa. Hints and the VC Dimension. Neural Computation, 5(2):278-288, 03 1993.
[2] Brandon Anderson, Truong Son Hy, and Risi Kondor. Cormorant: Covariant molecular neural networks. In H. Wallach, H. Larochelle, A. Beygelzimer, F. dAlché-Buc, E. Fox, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 32. Curran Associates, Inc., 2019.
[3] Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, and Tomaso A. Poggio. Unsupervised learning of invariant representations in hierarchical architectures. CoRR, abs/1311.4158, 2013.
[4] Fabio Anselmi, Lorenzo Rosasco, and Tomaso Poggio. On invariance and selectivity in representation learning. Information and Inference: A Journal of the IMA, 5(2):134-158, 05 2016.
[5] Minkyung Baek, Frank Dimaio, Ivan V. Anishchenko, Justas Dauparas, Sergey Ovchinnikov, Gyu Rie Lee, Jue Wang, Qian Cong, Lisa N. Kinch, R. Dustin Schaeffer, Claudia Millan, Hahnbeom Park, Carson Adams, Caleb R. Glassman, Andy M. DeGiovanni, Jose H. Pereira, Andria V. Rodrigues, Alberdina Aike van Dijk, Ana C Ebrecht, Diederik Johannes Opperman, Theo Sagmeister, Christoph Buhlheller, Tea Pavkov-Keller, Manoj K. Rathinaswamy, Udit Dalwadi, Calvin K. Yip, John E. Burke, K. Christopher Garcia, Nick V. Grishin, Paul D. Adams, Randy J. Read, and David Baker. Accurate prediction of protein structures and interactions using a three-track neural network. Science, 373:871 - 876, 2021.
[6] Peter Bartlett. Covering numbers, chaining & dudley's entropy integral (lecture 24). class notes on statistical learning theory, 2006.
[7] Arash Behboodi, Gabriele Cesa, and Taco S Cohen. A pac-bayesian generalization bound for equivariant networks. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh, editors, Advances in Neural Information Processing Systems, volume 35, pages 5654-5668. Curran Associates, Inc., 2022.
[8] Erik J. Bekkers. B-spline cnns on lie groups. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net, 2020.
[9] Alberto Bietti, Luca Venturi, and Joan Bruna. On the sample complexity of learning under geometric stability. Advances in neural information processing systems, 34:18673-18684, 2021.
[10] Olivier Bousquet, Stéphane Boucheron, and Gábor Lugosi. Introduction to statistical learning theory. Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures, pages 169-207, 2004.
[11] Anadi Chaman and Ivan Dokmanic. Truly shift-invariant convolutional neural networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 3773-3783, 2021.
[12] Shuxiao Chen, Edgar Dobriban, and Jane H Lee. A group-theoretic framework for data augmentation. The Journal of Machine Learning Research, 21(1):9885-9955, 2020.
[13] Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, and Max Welling. Gauge equivariant convolutional networks and the icosahedral cnn. In ICML, 2019.
[14] Taco Cohen and Max Welling. Group equivariant convolutional networks. In ICML, 2016.
[15] Taco S. Cohen. Learning transformation groups and their invariants. Master's thesis, University of Amsterdam, 2013.