Gaussian processes

…Wide networks behave like Gaussian processes and share features with free or weakly interacting fields. Focusing on one-dimensional field theories gives enough control to show, under mild assumptions, that any quantum-particle model has a neural-network representation. Architectural choices that satisfy quantum axioms then produce properties such as uncertainty relations. The presentation draws on joint work with Jim Halverson.

…In this work, we develop the Gaussian Process Linear Dy

Neural systems form high-dimensional representations that underpin their computational capabilities. Consequently, methods for quantifying representational similarity in neural representations have become a popular tool for identifying computational principles that are potentially shared across neural systems. These methods generally assume that neural responses are deterministic and static. However, responses of biological systems are noisy and dynamically unfold over time and these characteristics can have substantial influence on a system’s computational capabilities. We first show that exi

…nonparametric approaches such as Gaussian Processes (GPs) are highly flexible, expressive, and allow us to encode broad assumptions such as periodicity, stationarity, and smoothness. Though, these properties make GPs attractive for neural data analysis, their comput