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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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Compressing Deep ODE-Nets using Basis Function Expansions., , , and . CoRR, (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)Multiplicative Noise and Heavy Tails in Stochastic Optimization., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 4262-4274. PMLR, (2021)Generalization Guarantees via Algorithm-dependent Rademacher Complexity., , , , and . COLT, volume 195 of Proceedings of Machine Learning Research, page 4863-4880. PMLR, (2023)Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 13085-13117. PMLR, (2023)Stochastic continuous normalizing flows: training SDEs as ODEs., , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1130-1140. AUAI Press, (2021)Stochastic Normalizing Flows., , , and . CoRR, (2020)A PAC-Bayesian Perspective on the Interpolating Information Criterion., , , , and . CoRR, (2023)Taxonomizing local versus global structure in neural network loss landscapes., , , , , , and . NeurIPS, page 18722-18733. (2021)Noisy Recurrent Neural Networks., , , and . NeurIPS, page 5124-5137. (2021)