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Reverse engineering learned optimizers reveals known and novel mechanisms., , , , and . CoRR, (2020)Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers., , , , and . CoLLAs, volume 199 of Proceedings of Machine Learning Research, page 142-164. PMLR, (2022)Finite Versus Infinite Neural Networks: an Empirical Study., , , , , , and . NeurIPS, (2020)Adversarial Examples that Fool both Computer Vision and Time-Limited Humans., , , , , , and . NeurIPS, page 3914-3924. (2018)Score-Based Generative Modeling through Stochastic Differential Equations., , , , , and . ICLR, OpenReview.net, (2021)Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 8926-8945. PMLR, (2022)Adversarial Reprogramming of Neural Networks., , and . ICLR (Poster), OpenReview.net, (2019)Generalizing Hamiltonian Monte Carlo with Neural Networks., , and . ICLR (Poster), OpenReview.net, (2018)Guided evolutionary strategies: augmenting random search with surrogate gradients., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4264-4273. PMLR, (2019)Small-scale proxies for large-scale Transformer training instabilities., , , , , , , , , and 6 other author(s). ICLR, OpenReview.net, (2024)