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The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5042-5051. PMLR, (2019)A RAD approach to deep mixture models., , , and . DGS@ICLR, OpenReview.net, (2019)Meta-Learning Update Rules for Unsupervised Representation Learning., , , and . ICLR, OpenReview.net, (2019)Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes., , , , , , , , and . ICLR (Poster), OpenReview.net, (2019)Neural Tangents: Fast and Easy Infinite Neural Networks in Python., , , , , , and . CoRR, (2019)Is Batch Norm unique? An empirical investigation and prescription to emulate the best properties of common normalizers without batch dependence., and . CoRR, (2020)Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves., , , , and . CoRR, (2020)Language Model Cascades, , , , , , , , , and 2 other author(s). (2022)cite arxiv:2207.10342Comment: Presented as spotlight at the Beyond Bases workshop at ICML 2022 (https://beyond-bayes.github.io).Adversarial Examples that Fool both Computer Vision and Time-Limited Humans., , , , , , and . NeurIPS, page 3914-3924. (2018)Using a thousand optimization tasks to learn hyperparameter search strategies., , , , , and . CoRR, (2020)