Most problems studied in artificial intelligence possess some form of structure, but a precise way to define such structure is so far lacking. We investigate how the notion of pr...
Anthony Bucci, Jordan B. Pollack, Edwin D. de Jong
Abstract. We address the problem of learning good features for understanding video data. We introduce a model that learns latent representations of image sequences from pairs of su...
Abstract. Fluoroscopic images contain useful information that is difficult to comprehend due to the collapse of the 3D information into 2D space. Extracting the informative layers ...
Randomness is a necessary ingredient in various computational tasks and especially in Cryptography, yet many existing mechanisms for obtaining randomness suffer from numerous pro...
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...