SlowGuess/NeurIPS_2023_OCR huggingface dataset:
Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, and Taco Cohen. 3d steerable cnns: Learning rotationally equivariant features in volumetric data. arXiv preprint arXiv:1807.02547, 2018.
Daniel E Worrall, Stephan J Garbin, Daniyar Turmukhambetov, and Gabriel J Brostow. Harmonic networks: Deep translation and rotation equivariance. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 5028-5037, 2017.
Jin Xu, Hyunjik Kim, Thomas Rainforth, and Yee Teh. Group equivariant subsampling. Advances in Neural Information Processing Systems, 34:5934-5946, 2021.
Jianke Yang, Robin Walters, Nima Dehmamy, and Rose Yu. Generative adversarial symmetry discovery. arXiv preprint arXiv:2302.00236, 2023.
Raymond A Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, and Alexander Schwing. Equivariance discovery by learned parameter-sharing. In International Conference on Artificial Intelligence and Statistics, pages 1527-1545. PMLR, 2022.
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, and Alexander Smola. Deep sets. arXiv preprint arXiv:1703.06114, 2017.
Allan Zhou, Tom Knowles, and Chelsea Finn. Meta-learning symmetries by reparameterization. arXiv preprint arXiv:2007.02933, 2020.
Hongpeng Zhou, Minghao Yang, Jun Wang, and Wei Pan. Bayesnas: A bayesian approach for neural architecture search. In International conference on machine learning, pages 7603-7613. PMLR, 2019.
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le. Learning transferable architectures for scalable image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 8697-8710, 2018.