57 citations · 57 across the 2 of their papers we have counts for
3 papers · 1 filter
Deep Gaussian Processes
Andreas C. Damianou, Neil D. Lawrence
In this paper we introduce deep Gaussian process (GP) models. Deep GPs are a deep belief network based on Gaussian process mappings. The data is modeled as the output of a multivar…
Variational Gaussian Process Dynamical Systems
Andreas C. Damianou, Michalis K. Titsias, Neil D. Lawrence
High dimensional time series are endemic in applications of machine learning such as robotics (sensor data), computational biology (gene expression data), vision (video sequences)…
Residual Component Analysis
Alfredo A. Kalaitzis, Neil D. Lawrence
Probabilistic principal component analysis (PPCA) seeks a low dimensional representation of a data set in the presence of independent spherical Gaussian noise, Sigma = (sigma^2)*I.…