Results 11 to 20 of about 12,927,533 (245)
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions [PDF]
Entropy, 2014 Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Samuel Livingstone, Mark Girolami
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High performance Monte Carlo computation for finance risk data analysis [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Finance risk management has been playing an increasingly important role in the finance sector, to analyse finance data and to prevent any potential crisis ...
Zhao, Yu
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Crossed source-detector geometry for a novel spray diagnostic: Monte Carlo simulation and analytical results [PDF]
, 2005 Sprays and other industrially relevant turbid media can be quantitatively characterized by light scattering. However, current optical diagnostic techniques generate errors in the intermediate scattering regime where the average number of light ...
Churmakov, D. Y. +4 more
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Multilevel Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics [PDF]
, 2012 We show how to extend a recently proposed multi-level Monte Carlo approach to the continuous time Markov chain setting, thereby greatly lowering the computational complexity needed to compute expected values of functions of the state of the system to a ...
Anderson, David, Higham, Desmond
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SMCTC : sequential Monte Carlo in C++ [PDF]
, 2009 Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature.
Johansen, Adam M., Adam M. Johansen
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Geodesic Monte Carlo on Embedded Manifolds [PDF]
, 2013 Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows
Simon Byrne +5 more
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Markov chain Monte Carlo methods for state-space models with point process observations [PDF]
, 2012 This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations.
Niranjan, Mahesan +2 more
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The road to a modernized NJOY [PDF]
EPJ Web of ConferencesThe modernized version of the NJOY Nuclear Data Processing System is being built from a series of components that enable the traditional work required of the production version of NJOY while also providing a much more interactive user experience through ...
Haeck Wim +3 more
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Monte Carlo methods for TMD analyses
EPJ Web of Conferences, 2015 Monte Carlo simulations are an indispensable tool in experimental high-energy physics. Indeed, many discoveries rely on realistic modeling of background processes.
Schnell Gunar
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Monte Carlo Methods and the Koksma-Hlawka Inequality
Mathematics, 2019 The solution of a wide class of applied problems can be represented as an integral over the trajectories of a random process. The process is usually modeled with the Monte Carlo method and the integral is estimated as the average value of a certain ...
Sergey Ermakov, Svetlana Leora
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