
NonFactorised Variational Inference in Dynamical Systems
We focus on variational inference in dynamical systems where the discret...
read it

Overcoming MeanField Approximations in Recurrent Gaussian Process Models
We identify a new variational inference scheme for dynamical systems who...
read it

Convolutional Gaussian Processes
We present a practical way of introducing convolutional structure into G...
read it

Understanding Probabilistic Sparse Gaussian Process Approximations
Good sparse approximations are essential for practical inference in Gaus...
read it

DataEfficient Reinforcement Learning in ContinuousState POMDPs
We present a dataefficient reinforcement learning algorithm resistant t...
read it

Gaussian Processes for DataEfficient Learning in Robotics and Control
Autonomous learning has been a promising direction in control and roboti...
read it

Manifold Gaussian Processes for Regression
Offtheshelf Gaussian Process (GP) covariance functions encode smoothne...
read it

Integrated PreProcessing for Bayesian Nonlinear System Identification with Gaussian Processes
We introduce GPFNARX: a new model for nonlinear system identification b...
read it

Robust Filtering and Smoothing with Gaussian Processes
We propose a principled algorithm for robust Bayesian filtering and smoo...
read it

Additive Gaussian Processes
We introduce a Gaussian process model of functions which are additive. A...
read it

Deep Convolutional Networks as shallow Gaussian Processes
We show that the output of a (residual) convolutional neural network (CN...
read it

Closedform Inference and Prediction in Gaussian Process StateSpace Models
We examine an analytic variational inference scheme for the Gaussian Pro...
read it

PIPPS: Flexible ModelBased Policy Search Robust to the Curse of Chaos
Previously, the exploding gradient problem has been explained to be cent...
read it

Benchmarking the Neural Linear Model for Regression
The neural linear model is a simple adaptive Bayesian linear regression ...
read it

Approximate Inference for Fully Bayesian Gaussian Process Regression
Learning in Gaussian Process models occurs through the adaptation of hyp...
read it
Carl Edward Rasmussen
is this you? claim profile