Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Lei...
We present a data-driven technique for generating the precomputed radiance transfer vectors of an animated character as a function of its joint angles. We learn a linear model for...
Derek Nowrouzezahrai, Patricio D. Simari, Evangelo...
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Spectral clustering and eigenvector-based methods have become increasingly popular in segmentation and recognition. Although the choice of the pairwise similarity metric (or affin...
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...