We consider the problem of estimating the small probability that a function of a finite number of random variables exceeds a large threshold. Each input random variable may be lig...
In recent years particle ...lters have been applied to a variety of state estimation problems. A particle ...lter is a sequential Monte Carlo Bayesian estimator of the posterior d...
We present a new approach to runtime verification that utilizes classical statistical techniques such as Monte Carlo simulation, hypothesis testing, and confidence interval estima...
Sean Callanan, Radu Grosu, Abhishek Rai, Scott A. ...
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
In this paper we present Poisson sum series representations for α-stable (αS) random variables and α-stable processes, in particular concentrating on continuous-time autoregres...