20 citations · 34 across the 4 of their papers we have counts for
4 papers
Learning Direct Optimization for Scene Understanding
Lukasz Romaszko, Christopher K. I. Williams, John Winn
We develop a Learning Direct Optimization (LiDO) method for the refinement of a latent variable model that describes input image x. Our goal is to explain a single image x with an…
Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering
Liwen Zhang, John Winn, Ryota Tomioka
We propose the Gaussian attention model for content-based neural memory access. With the proposed attention model, a neural network has the additional degree of freedom to control…
Consensus Message Passing for Layered Graphical Models
Varun Jampani, S. M. Ali Eslami, Daniel Tarlow +2
Generative models provide a powerful framework for probabilistic reasoning. However, in many domains their use has been hampered by the practical difficulties of inference. This is…
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Nicolas Heess, Nicolas Le Roux, John Winn
We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled independently o…