Non-reversible Gaussian processes for identifying latent dynamical structure in neural data

no code implementations • NeurIPS 2020 • Virginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin

Here, we propose a new family of “dynamical” priors over trajectories, in the form of GP covariance functions that express a property shared by most dynamical systems: temporal non-reversibility.

Gaussian Processes Model Selection +1