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Continuous-time Markov chain
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1	TASK The arrival of new customers is modeled in the following way. Let X_t be a continuous time Markov chain, which occupies state i at time 0. Conditional on all the future dynamics of X_t, process N_t is a Poisson proc Add to Reading List Source URL: www.stanfordphd.com Language: English - Date: 2018-02-16 02:18:47
2	Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Add to Reading List Source URL: www.cs.huji.ac.il Language: English - Date: 2015-08-10 08:23:20 Bayesian statistics Statistics Graphical models Probability Markov models Bayesian network Probability distribution Markov chain Expectation propagation Approximate inference Likelihood function Hidden Markov model
3	Journal of Artificial Intelligence Research–774 Submitted 03/10; publishedIntrusion Detection using Continuous Time Bayesian Networks Jing Xu Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:19 Statistics Estimation theory Control theory Mathematical analysis Markov models Graphical models Bayesian network Maximum likelihood estimation Expectationmaximization algorithm Markov chain Discretization State-space representation
4	Learning Continuous-Time Social Network Dynamics Yu Fan University of California, Riverside Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:15 Statistics Estimation theory Markov models Statistical theory Statistical models Regression analysis Bayesian network Gibbs sampling Markov chain Expectationmaximization algorithm Parameter Mathematical model
5	Factored Filtering of Continuous-Time Systems E. Busra Celikkaya Christian R. Shelton University of California, Riverside University of California, Riverside Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-06-23 16:38:35 Markov models Markov processes KullbackLeibler divergence Statistical theory Thermodynamics Probability distributions Uniformization Expectationmaximization algorithm Markov chain Bayesian network Stochastic matrix
6	Journal of Machine Learning Research2140 Submitted 3/09; Revised 6/10; Published 8/10 Importance Sampling for Continuous Time Bayesian Networks Yu Fan Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:14 Markov models Probability distributions Graphical models Monte Carlo methods Stochastic simulation Bayesian network Markov chain Importance sampling Gibbs sampling Exponential distribution Cumulative distribution function Variance
7	UNIVERSITY OF CALIFORNIA RIVERSIDE Continuous Time Bayesian Network Approximate Inference and Social Network Applications Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:15 Monte Carlo methods Stochastic simulation Computational statistics Markov models Markov chain Monte Carlo Bayesian network Gibbs sampling Particle filter Approximate inference Expectationmaximization algorithm Statistics Importance sampling
8	A General Framework for Pricing Asian Options Under Markov Processes Add to Reading List Source URL: www.rmi.nus.edu.sg Language: English - Date: 2015-07-02 21:04:44 Options Stochastic processes Mathematical finance Asian option BlackScholes model Continuous-time Markov chain Barrier option Stochastic volatility Markov process Jump process
9	CS168: The Modern Algorithmic Toolbox Lecture #14: Markov Chain Monte Carlo Tim Roughgarden & Gregory Valiant∗ May 11, 2016 The previous lecture covered several tools for inferring properties of the distribution that u Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-06-04 09:49:43 Markov models Markov processes Stochastic processes Monte Carlo methods Statistical mechanics Markov chain Stochastic matrix Markov property Random walk Continuous-time Markov chain Bayesian inference in phylogeny
10	The Dynamics of Distributions in Continuous-Time Stochastic Models (a) Christian Bayer(a) and Klaus Wälde(b) WeierstraßInstitute Berlin and (b) Johannes-Gutenberg University Mainz1 Add to Reading List Source URL: www.waelde.com Language: English - Date: 2015-11-27 06:04:16 Stochastic processes Markov chain FokkerPlanck equation Markov process Markov kernel Probability distribution Brownian motion It diffusion Bellman equation