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Importance sampling
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#	Item
71	Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation David Wingate Andreas Stuhlmüller Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2011-06-30 04:29:48 Monte Carlo methods Statistical models Importance sampling Variance reduction Stochastic process Markov chain Monte Carlo Mixture model Markov chain Kalman filter Statistics Probability and statistics Markov models
72	Part A Simulation and Statistical Programming, HT 2015 Simulation lectures Matti Vihola March 9, 2015 Add to Reading List Source URL: www.stats.ox.ac.uk Language: English - Date: 2015-03-09 12:17:45 Probability theory Normal distribution Central limit theorem Multivariate normal distribution Cumulative distribution function Importance sampling Independence Random variable Uniform distribution Statistics Mathematical analysis Mathematics
73	The Monte-Carlo Parametric Expectation Maximization Algorithm Add to Reading List Source URL: www.cognigencorp.com Language: English - Date: 2009-05-12 17:23:03 Maximum likelihood Importance sampling Statistics Statistical theory Estimation theory
74	Adaptive Monte Carlo via Bandit Allocation James Neufeld JNEUFELD @ UALBERTA . CA Andr´as Gy¨orgy GYORGY @ UALBERTA . CA Dale Schuurmans Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2014-05-18 17:42:18 Monte Carlo methods Statistical theory Decision theory Estimator M-estimator Importance sampling Mean squared error Bias of an estimator Regret Statistics Estimation theory Statistical inference
75	Scaling-up Importance Sampling for Markov Logic Networks Vibhav Gogate Department of Computer Science University of Texas at Dallas Add to Reading List Source URL: www.hlt.utdallas.edu Language: English - Date: 2014-10-31 21:56:53 Monte Carlo methods Data analysis Artificial intelligence Markov logic network Gibbs sampling Importance sampling Bayesian inference Sampling First-order logic Statistics Statistical inference Bayesian statistics
76	Monte Carlo Methods in Particle Physics Bryan Webber University of Cambridge IMPRS, MunichNovember 2007 Add to Reading List Source URL: www.hep.phy.cam.ac.uk Language: English - Date: 2007-11-11 13:20:43 Probability and statistics Applied mathematics Numerical analysis Event generator Importance sampling Hadronization Quasi-Monte Carlo method Monte Carlo methods in finance Monte Carlo methods Physics Computational physics
77	Approximate Counting by Sampling the Backtrack-free Search Space Vibhav Gogate and Rina Dechter Donald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, {vgogate,dechter}@ics.uc Add to Reading List Source URL: sami.ics.uci.edu Language: English - Date: 2007-08-17 19:31:44 Computing Partial differential equations Importance sampling Variance reduction Lookup table Monte Carlo integration Boolean satisfiability problem Monte Carlo methods Theoretical computer science Mathematics
78	Peer-review e-journal «Problemi telekomunìkacìj» • № 3 (15) • 2014 • http://pt.journal.kh.ua Add to Reading List Source URL: pt.journal.kh.ua Language: English - Date: 2015-03-23 03:02:01 Wiener process Random variable Stochastic Kalman filter Importance sampling Statistics Stochastic processes Estimation theory
79	Importance of Client Data and Correct Sampling Procedures An important factor in solving your water problem is the relationship between the water quality of your sample and typical qualities for that type of water. Add to Reading List Source URL: www.sws.uiuc.edu Language: English - Date: 2011-09-30 12:42:42 Environmental science Water Water management Water quality Chemistry Sampling PSL Soft matter Matter Water pollution
80	MINIMAL PARTIAL PROXY SIMULATION SCHEMES FOR GENERIC AND ROBUST MONTE-CARLO GREEKS JIUN HONG CHAN AND MARK JOSHI Abstract. In this paper, we present a generic framework known as the minimal partial proxy simulation schem Add to Reading List Source URL: fbe.unimelb.edu.au Language: English - Date: 2013-08-05 02:06:38 Variance reduction Stochastic differential equation Statistics Stochastic processes Importance sampling

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