Pashupati Hegde

Deep learning with differential Gaussian process flows

2018 · Research Explorer (The University of Manchester)

We propose a novel deep learning paradigm of differential flows that learn a stochastic differential equation transformations of inputs prior to a standard classification or regression function. The key property of differential Gaussian processes is …

Variational multiple shooting for Bayesian ODEs with Gaussian processes

2021 · arXiv (Cornell University)

Recent machine learning advances have proposed black-box estimation of unknown continuous-time system dynamics directly from data. However, earlier works are based on approximative ODE solutions or point estimates. We propose a novel Bayesian nonparametric model …