An algorithm is presented for topology selection in graphical models of autoregressive Gaussian time series. The graph topology of the model represents the sparsity pattern of the...
We propose a convex optimization method for maximum likelihood estimation of autoregressive models, subject to conditional independence constraints. This problem is an extension t...
Jitkomut Songsiri, Joachim Dahl, Lieven Vandenberg...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density ...
We present a novel approach to motion synthesis. It is shown that by splitting sequences into segments new sequences can be created with a similar look and feel to the original. C...
David Oziem, Neill W. Campbell, Colin J. Dalton, D...