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Stochastic continuous normalizing flows: training SDEs as ODEs.

, , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1130-1140. AUAI Press, (2021)

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Generalization Properties of Stochastic Optimizers via Trajectory Analysis., , , and . CoRR, (2021)The Interpolating Information Criterion for Overparameterized Models., , , , and . CoRR, (2023)Compressing Deep ODE-Nets using Basis Function Expansions., , , and . CoRR, (2021)Multiplicative Noise and Heavy Tails in Stochastic Optimization., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 4262-4274. PMLR, (2021)Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 8774-8795. PMLR, (2022)Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes., , , and . CoRR, (2022)When are ensembles really effective?, , , , and . CoRR, (2023)Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data., , , , , , and . KDD, page 3011-3021. ACM, (2023)Stateful ODE-Nets using Basis Function Expansions., , , and . NeurIPS, page 21770-21781. (2021)Lipschitz Recurrent Neural Networks., , , , and . ICLR, OpenReview.net, (2021)