The Recurrent Temporal Restricted Boltzmann Machine Ilya Sutskever, Geoffrey Hinton, and Graham Taylor University of Toronto {ilya, hinton, gwtaylor}@cs.utoronto.ca

Source URL: papers.nips.cc

• Neural networks
• Science
• Bayesian statistics
• Boltzmann machine
• Markov models
• Probability theory
• Hidden Markov model
• Belief propagation
• Information theory
• Statistics
• Graphical models
• Mathematics

Hybrid Variational/Gibbs Collapsed Inference in Topic Models Max Welling∗ Dept. Computer Science University of California Irvine Irvine, CA, USA

Source URL: www.ics.uci.edu

• Variational Bayesian methods
• Expectation–maximization algorithm
• Gibbs sampling
• Bayesian network
• Centimetre–gram–second system of units
• Belief propagation
• Bayesian inference
• Latent Dirichlet allocation
• Perplexity
• Statistics
• Bayesian statistics
• Graphical models

Building Dynamic Knowledge Graphs Lise Getoor Department of Computer Science University of California Santa Cruz, CA 95064

Source URL: www.akbc.ws

• Statistics
• Statistical models
• Graph theory
• Theoretical computer science
• Algorithm
• Mathematical model
• Bayesian network
• Factor graph
• Mathematics
• Graphical models
• Bayesian statistics

Generalized Belief Propagation on Tree Robust Structured Region Graphs Andrew E. Gelfand Dept. of Computer Science University of California, Irvine Irvine, CA, USA

Source URL: www.ics.uci.edu

• Algebraic graph theory
• Matroid theory
• Cycle space
• Line graph
• Factor graph
• Graph
• Planar graph
• Spanning tree
• Tree decomposition
• Graph theory
• Graph operations
• Graphical models

THIS IS A DRAFT VERSION. FINAL VERSION TO BE PUBLISHED AT NIPS ’06 Structure Learning in Markov Random Fields Sridevi Parise Bren School of Information and Computer Science

Source URL: www.ics.uci.edu

• Probability theory
• Estimation theory
• Graphical models
• Marginal likelihood
• Expectation–maximization algorithm
• Variational Bayesian methods
• Normal distribution
• Maximum likelihood
• Bayesian network
• Statistics
• Bayesian statistics
• Statistical theory

Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study Sanjiv Kumar, Jonas August, and Martial Hebert The Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15213

Source URL: www.sanjivk.com

• Graphical models
• Bayesian statistics
• Probability theory
• Maximum likelihood
• Likelihood function
• Conditional random field
• Belief propagation
• Statistics
• Estimation theory
• M-estimators

Modelling Relational Data using Bayesian Clustered Tensor Factorization Ilya Sutskever University of Toronto

Source URL: papers.nips.cc

• Linear filters
• Estimation theory
• Tensor
• Graphical model
• Ensemble Kalman filter
• Statistics
• Bayesian statistics
• Statistical models

Comparative Evaluation of different Graphical Models for the Analysis of Gene Expression Data Doctoral Thesis Submitted to the Department of Statistics

Source URL: eldorado.tu-dortmund.de

Graphical models Markov properties for directed acyclic graphs Causal Bayesian networks Structural equation systems Computation of effects References

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

Lecture 12: Graphical models for Text 4F13: Machine Learning Carl Edward Rasmussen and Zoubin Ghahramani Department of Engineering University of Cambridge

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