This paper investigates the use of the Bayesian inference for devising an example-based rendering procedure. As prior model of this Bayesian inference, we exploit the multiscale n...
Abstract— Imitation learning, or programming by demonstration (PbD), holds the promise of allowing robots to acquire skills from humans with domain-specific knowledge, who nonet...
:We formulate structure from motion as a Bayesian inference problem, and use a Markov chain Monte Carlo sampler to sample the posterior on this problem. This results in a method th...
Image priors based on products have been recognized to offer many advantages because they allow simultaneous enforcement of multiple constraints. However, they are inconvenient for...
Giannis K. Chantas, Nikolas P. Galatsanos, Aristid...
We propose a non-parametric Bayesian model for unsupervised semantic parsing. Following Poon and Domingos (2009), we consider a semantic parsing setting where the goal is to (1) d...