Stan: A probabilistic programming language for Bayesian inference and optimization∗ Andrew Gelman† Daniel Lee†

Source URL: www.stat.columbia.edu

A New Efficient Probabilistic Model for Mining Labeled Ordered Trees Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka Bioinformatics Center, Institute for Chemical Research, K

Source URL: www.bic.kyoto-u.ac.jp

• Markov models
• Computer programming
• Software engineering
• Binary trees
• Computing
• Graphical models
• Bioinformatics
• Bayesian network
• Hidden Markov model
• Rope
• Markov chain
• Probability distribution

Robustness and U.S. Monetary Policy Experimentation∗ Timothy Cogley† Riccardo Colacito‡ Lars Peter Hansen§ Thomas J. Sargent¶

Source URL: www.tomsargent.com

• Decision theory
• Control theory
• Mathematical optimization
• Dynamic programming
• Bellman equation
• Thomas J. Sargent
• Loss function
• Prior probability
• Hyperparameter
• Statistics
• Bayesian statistics
• Economics

A New Approach to Probabilistic Programming Inference Frank Wood Department of Engineering University of Oxford

Source URL: www.robots.ox.ac.uk

• Statistical theory
• Bayesian statistics
• Statistical inference
• Hidden Markov model
• Importance sampling
• Normal distribution
• Mixture model
• Bayesian inference
• Joint probability distribution
• Statistics
• Probability and statistics
• Monte Carlo methods

Implementing Approximate Bayesian Inference using Integrated Nested Laplace Approximation: a manual for the inla program Sara Martino and H˚avard Rue Department of Mathematical Sciences NTNU, Norway January 2008

Source URL: www.bias-project.org.uk

• C programming language
• International Obfuscated C Code Contest
• Expectation–maximization algorithm
• Computer programming
• Computing
• Statistics

ON-LINE POLICY OPTIMISATION OF BAYESIAN SPOKEN DIALOGUE SYSTEMS VIA HUMAN INTERACTION M. Gaˇsi´c, C. Breslin, M. Henderson, D. Kim, M. Szummer, B. Thomson, P. Tsiakoulis and S. Young Cambridge University Engineering De

Source URL: mi.eng.cam.ac.uk

• Stochastic control
• Bayesian statistics
• Partially observable Markov decision process
• Simulation
• Gaussian process
• Dialogue
• Markov decision process
• Machine learning
• Supervised learning
• Statistics
• Dynamic programming
• Markov processes

Bayesian Learning of Recursively Factored Environments Marc Bellemare Joel Veness Michael Bowling University of Alberta, Edmonton, Canada, T6G 2E8

Source URL: jveness.info

• Science
• Graphical model
• Hidden Markov model
• Factorization
• Dynamic programming
• Recursion
• Mathematics
• Statistics
• Markov models

Advances in Bayesian Network Learning using Integer Programming Mark Barlett Dept of Computer Science & York Centre for Complex Systems Analysis University of York, UK

Source URL: www.cs.york.ac.uk

• Mathematics
• Linear programming
• Constraint programming
• Convex optimization
• Combinatorial optimization
• Linear programming relaxation
• Cutting-plane method
• Bayesian network
• SCIP
• Mathematical optimization
• Operations research
• Applied mathematics

COMPSCI 276 Homework Assignment 4 Fall 2014 Instructor: Rina Dechter Due:Wednesday, November 5th

Source URL: www.ics.uci.edu

• Statistical models
• Bayesian network
• Networks
• Ordered graph
• Mathematical sciences
• Mathematics
• Bayesian statistics
• Constraint programming
• Graphical models

Netica-J Reference Manual

Source URL: www.norsys.com

• Java
• Bayesian network
• Application programming interface
• Computing
• Cross-platform software
• Java platform