In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Decentralized MDPs provide powerful models of interactions in multi-agent environments, but are often very difficult or even computationally infeasible to solve optimally. Here we...
Background: Noise has many important roles in cellular genetic regulatory functions at the nanomolar scale. At present, no good theory exists for identifying all possible mechanis...
A self-organizing neural network for learning and recall of complex temporal sequences is proposed. we consider a single sequence with repeated items, or several sequences with a c...
Abstract. We propose a new framework for simulating blood flow inside the heart, usable with geometric models of the heart from patientspecific data. The method is geared toward re...
Viorel Mihalef, Dimitris N. Metaxas, Mark Sussman,...