Robust tracking of abrupt motion is a challenging task
in computer vision due to the large motion uncertainty. In
this paper, we propose a stochastic approximation Monte
Carlo (...
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
In this paper, we propose a new stereo matching method using the population-based Markov Chain Monte Carlo (Pop-MCMC), which belongs to the sampling-based methods. Since the previo...
Wonsik Kim (Seoul National University), Joonyoung ...
Abstract--The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov C...
Jonathan M. R. Byrd, Stephen A. Jarvis, Abhir H. B...
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementat...