—We present a new technique for statistical static timing analysis (SSTA) based on Markov chain Monte Carlo (MCMC), that allows fast and accurate estimation of the right-hand tai...
Yashodhan Kanoria, Subhasish Mitra, Andrea Montana...
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...
Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...
Abstract. In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on new criteria evaluating the qu...
Reversible jump Markov chain Monte Carlo (RJMCMC) is a recent method which makes it possible to construct reversible Markov chain samplers that jump between parameter subspaces of...