Aeolus: A Markov–Chain Monte Carlo code for mapping

Aeolus: a Markov Chain Monte Carlo Code for Mapping Ultracool Atmospheres. an Application on Jupiter and Brown Dwarf Hst Light Curves

Deducing the cloud cover and its temporal evolution from the observed planetary spectra and phase curves can give us major insight into the atmospheric dynamics. In this paper, we present Aeolus, a Markovchain Monte Carlo code that maps the structure of brown dwarf and other ultracool atmospheres. We validated Aeolus on a set of unique Jupiter Hubble Space Telescope (HST) light curves. Aeolus ...

Slice Samoling as a Markov Chain Monte Carlo Method

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A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping

A Markov-chain Monte Carlo based algorithm is provided to solve the Simultaneous localization and mapping (SLAM) problem with general dynamics and observation model under open-loop control and provided that the map-representation is finite dimensional. To our knowledge this is the first provably consistent yet (close-to) practical solution to this problem. The superiority of our algorithm over ...

Automatic Recognition and Location of Civil Infrastructure Objects Using Mobile Mapping Technology, Neural Network and Markov Chain Monte Carlo

A Stochastic algorithm to solve multiple dimensional Fredholm integral equations of the second kind

In the present work‎, ‎a new stochastic algorithm is proposed to solve multiple dimensional Fredholm integral equations of the second kind‎. ‎The solution of the‎ integral equation is described by the Neumann series expansion‎. ‎Each term of this expansion can be considered as an expectation which is approximated by a continuous Markov chain Monte Carlo method‎. ‎An algorithm is proposed to sim...