65 citations · 247 across the 12 of their papers we have counts for
3 papers · 1 filter
Convolutional Gaussian Processes
Mark van der Wilk, Carl Edward Rasmussen, James Hensman
We present a practical way of introducing convolutional structure into Gaussian processes, making them more suited to high-dimensional inputs like images. The main contribution of…
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction
Hossein Soleimani, James Hensman, Suchi Saria
Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation met…
Identification of Gaussian Process State Space Models
Stefanos Eleftheriadis, Thomas F. W. Nicholson, Marc Peter Deisenroth +1
The Gaussian process state space model (GPSSM) is a non-linear dynamical system, where unknown transition and/or measurement mappings are described by GPs. Most research in GPSSMs…