[38] Chirag Pabbaraju, Ezra Winston, and J Zico Kolter. Estimating lipschitz constants of monotone deep equilibrium models. In ICLR, 2021.
[39] Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. Pytorch: An imperative style, high-performance deep learning library. In NeurIPS, 2019.
[40] Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, and Ming Lin. Scalable differentiable physics for learning and control. In ICML, 2020.
[41] Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. You only look once: Unified, real-time object detection. In CVPR, 2016.
[42] Max Revay, Ruigang Wang, and Ian R Manchester. Lipschitz bounded equilibrium networks. arXiv preprint arXiv:2010.01732, 2020.
[43] Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. The graph neural network model. IEEE transactions on neural networks, 20(1):61-80, 2008.
[44] Bernhard Scholkopf, Kah-Kay Sung, Christopher JC Burges, Federico Girosi, Partha Niyogi, Tomaso Poggio, and Vladimir Vapnik. Comparing support vector machines with gaussian kernels to radial basis function classifiers. IEEE transactions on Signal Processing, 45(11):2758-2765, 1997.
[45] Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. Grad-cam: Visual explanations from deep networks via gradient-based localization. In ICCV, 2017.
[46] Ivana Tošić and Pascal Frossard. Dictionary learning. IEEE Signal Processing Magazine, 28(2):27-38, 2011.
[47] Asher Trockman and J Zico Kolter. Patches are all you need? arXiv preprint arXiv:2201.09792, 2022.
[48] Russell Tsuchida, Fred Roosta, and Marcus Gallagher. Invariance of weight distributions in rectified mlp's. In ICML, 2018.
[49] Russell Tsuchida, Suk Yee Yong, Mohammad Ali Armin, Lars Petersson, and Cheng Soon Ong. Declarative nets that are equilibrium models. In ICLR, 2022.
[50] Po-Wei Wang, Priya Donti, Bryan Wilder, and Zico Kolter. Satnet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. In ICML, 2019.
[51] Ezra Winston and J Zico Kolter. Monotone operator equilibrium networks. In NeurIPS, 2020.
[52] Xingyu Xie, Qiuhao Wang, Zenan Ling, Xia Li, Guangcan Liu, and Zhouchen Lin. Optimization induced equilibrium networks: An explicit optimization perspective for understanding equilibrium models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3):3604-3616, 2022.
[53] Xingyu Xie, Jianlong Wu, Guangcan Liu, Zhisheng Zhong, and Zhouchen Lin. Differentiable linearized admm. In ICML, 2019.
[54] Chong You, Daniel Robinson, and René Vidal. Scalable sparse subspace clustering by orthogonal matching pursuit. In CVPR, 2016.
[55] Hongyang Zhang, Zhouchen Lin, Chao Zhang, and Edward Y Chang. Exact recoverability of robust pca via outlier pursuit with tight recovery bounds. In AAAI, 2015.
[56] Xiao Zhang, Lingxiao Wang, Yaodong Yu, and Quanquan Gu. A primal-dual analysis of global optimality in nonconvex low-rank matrix recovery. In ICML, 2018.
[57] Barret Zoph and Quoc V Le. Neural architecture search with reinforcement learning. arXiv preprint arXiv:1611.01578, 2016.