Temporal datasets, in which data evolves continuously, exist in a wide variety of applications, and identifying anomalous or outlying objects from temporal datasets is an importan...
he significant increase in the available computational power that took place in recent decades has been accompanied by a growing interest in the application of the evolutionary ap...
"A random or stochastic process is a mathematical model for a phenomenon
that evolves in time in an unpredictable manner from the viewpoint of the
observer. The phenomenon m...
The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this lowdimensional rep...
Particle filters encode a time-evolving probability density by maintaining a random sample from it. Level sets represent closed curves as zero crossings of functions of two variab...