55 citations · 97 across the 7 of their papers we have counts for
4 papers · 1 filter
Non-Factorised Variational Inference in Dynamical Systems
Alessandro Davide Ialongo, Mark van der Wilk, James Hensman +1
We focus on variational inference in dynamical systems where the discrete time transition function (or evolution rule) is modelled by a Gaussian process. The dominant approach so f…
Closed-form Inference and Prediction in Gaussian Process State-Space Models
Alessandro Davide Ialongo, Mark van der Wilk, Carl Edward Rasmussen
We examine an analytic variational inference scheme for the Gaussian Process State Space Model (GPSSM) - a probabilistic model for system identification and time-series modelling.…
Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks
Martin Trapp, Robert Peharz, Carl E. Rasmussen +1
While Gaussian processes (GPs) are the method of choice for regression tasks, they also come with practical difficulties, as inference cost scales cubic in time and quadratic in me…
Microfluidic pump driven by anisotropic phoresis
Zihan Tan, Mingcheng Yang, Marisol Ripoll
Fluid flow along microchannels can be induced by keeping opposite walls at different temperatures, and placing elongated tilted pillars inside the channel. The driving force for th…