Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
3D modeling of a free-form object involves the acquisition of multiple views (range images) of the object to cover its entire surface. These views are then registered in a common ...
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
In this paper we propose a generic framework based on Hidden Markov Models (HMMs) for recognition of individuals from their gait. The HMM framework is suitable, because the gait o...
Aravind Sundaresan, Amit K. Roy Chowdhury, Rama Ch...
This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action gra...