Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
A framework for photo-realistic view-dependent image synthesis of a shiny object from a sparse set of images and a geometric model is proposed. Each image is aligned with the 3D m...
In this paper, we first present a new implementation of the 3-D fast curvelet transform, which is nearly 2.5 less redundant than the Curvelab (wrapping-based) implementation as o...
Wavelets provide a sparse representation for piecewise smooth signals in 1-D; however, separable extensions of wavelets to multiple dimensions do not achieve the same level of spa...
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...