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cs.LG2023
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs
Kevin Course, Prasanth B. Nair
We consider the problem of inferring latent stochastic differential equations (SDEs) with a time and memory cost that scales independently with the amount of data, the total length…
cs.LG2021
Weak Form Generalized Hamiltonian Learning
Kevin L. Course, Trefor W. Evans, Prasanth B. Nair
We present a method for learning generalized Hamiltonian decompositions of ordinary differential equations given a set of noisy time series measurements. Our method simultaneously…