In this work we develop a new technique for over-approximating (in the sense of timed trace inclusion) continuous dynamical systems by timed auThis technique refines commonly-used ...
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...
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Randomness is inherent to biochemistry: at each instant, the sequence of reactions that fires is a matter of chance. Some biological systems exploit such randomness, choosing betw...
From the phosphorylation state of a molecule to the volume of a cell, parameters are ubiquitous in systems biology. At the same time, most models involve static or dynamic compart...