Dynamic Bayesian Networks: Representation, Inference and Learning (2002)

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by Kevin Patrick Murphy
Citations:564 - 3 self

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9 Time Series Learning with Probabilistic Network Composites – William Henry Hsu - 1998
Proposed design for gR, a graphical models toolkit for R – Kevin P. Murphy - 2003
249 Operations for Learning with Graphical Models – Wray L. Buntine - 1994
Graphical Models for Biclustering . . . – José Caldas - 2012
Data Modelling and Description: A Guide to Using the SYLModel Library – Jayson E. Rome, Alexei D. Miasnikov, Robert M. Haralick
1 Divide and Conquer: Pattern Recognition using Mixtures of Experts – Steve Waterhouse, Steve Waterhouse - 1997
1 Hidden Dynamic Models for Speech Processing Applications – Leo Jingyu Lee
Zdzisław and Jadwiga, – Richard Szeliski, Stephen Iv
67 Graphical models and automatic speech recognition – Jeffrey A. Bilmes - 2003
Bayesian Modelling in Machine Learning: A Tutorial Review – Matthias Seeger - 2009
Probabilistic Variational Methods for Vision based Complex Motion Analysis – Gang Hua
2 BAYESIAN MODELING OF MUSICAL EXPECTATIONS VIA MAXIMUM ENTROPY STOCHASTIC GRAMMARS – Randal J. Leistikow, Jonathan Berger, Julius O. Smith - 2006
48 Hybrid Bayesian Networks for Reasoning about Complex Systems – Uri N. Lerner - 2002
2 Machine Learning: A Probabilistic Approach – David Barber - 2006
3 Q.: Probabilistic image modeling with an extended chain graph for human activity recognition and image segmentation – Lei Zhang, Zhi Zeng, Qiang Ji, Senior Member - 2011
4 How to Implement A Priori Information: A Statistical Mechanics Approach – Jörg C. Lemm - 1998
Multi-rate Coupled Hidden Markov Models and Their Application to Machining Tool-Wear Classification – Özgür Çetin, Mari Ostendorf, Gary D. Bernard
22 Speech Recognition Using Augmented Conditional Random Fields – Yasser Hifny, Steve Renals
5 Technical Introduction: A Primer on Probabilistic Inference – Thomas L. Griffiths, Alan Yuille - 2006