A novel Monte Carlo noise reduction operator is proposed in this paper. We apply and extend the standard bilateral filtering method and build a new local adaptive noise reduction k...
Abstract— This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture...
Simulated annealing has been one of the most popular stochastic optimization methods used in the VLSI CAD field in the past two decades for handling NP-hard optimization problems...
Jason Cong, Tianming Kong, Faming Liang, Jun S. Li...
— Self-localization is a major research task in mobile robotics for several years. Efficient self-localization methods have been developed, among which probabilistic Monte-Carlo...
Background: The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progr...
Botond Sipos, Tim Massingham, Gregory E. Jordan, N...