We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
This paper addresses the probabilistic inference of geometric structures from images. Specifically, of synthesizing range data to enhance the reconstruction of a 3D model of an in...
Fundamental to case-based reasoning is the idea that similar problems have similar solutions. The meaning of the concept of "similarity" can vary in different situations...
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...