Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
When using Learning Object Repositories, it is interesting to have mechanisms to select the more adequate objects for each student. For this kind of adaptation, it is important to...
Cristina Carmona, Gladys Castillo, Eva Millá...
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...