Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
Fluid modelling is a next-generation technique for analysing massive performance models. Passive cooperation is a popular cooperation mechanism frequently used by performance engi...
Current stochastic model checkers do not make counterexamples for property violations readily available. In this paper we apply directed explicit state space search to discrete- a...
This paper presents a general gait representation framework for video-based human motion estimation. Specifically, we want to estimate the kinematics of an unknown gait from image ...