Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
We present an algorithm to infer causal relations between a set of measured variables on the basis of experiments on these variables. The algorithm assumes that the causal relatio...
Frederick Eberhardt, Patrik O. Hoyer, Richard Sche...
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...