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Corcoran, Jem Associate Professor

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Research

research overview

  • Dr. Corcoran's research is focused on Markov chain Monte Carlo (MCMC) algorithms with applications to problems in high-dimensional Bayesian network inference, target tracking, statistical mechanics, high-energy physics, and rarefied gas dynamics. Specifically, her contributions have involved the development of novel fast algorithms which bypass all or most convergence issues encountered in traditional MCMC simulations.

keywords

  • Monte Carlo algorithms, Recovering Bayesian Networks from Data and from Discretized Data, Particle Filtering and Target Tracking, Direct Simulation Monte Carlo for Rarefied Gas Dynamics

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