Classification and Regression using Mixtures of Experts (1997)

by Steven Richard Waterhouse
Citations:35 - 0 self

Active Bibliography

1 Divide and Conquer: Pattern Recognition using Mixtures of Experts – Steve Waterhouse, Steve Waterhouse - 1997
7 Prior Information and Generalized Questions – Jörg C. Lemm - 1996
Bayesian Modelling in Machine Learning: A Tutorial Review – Matthias Seeger - 2009
MLnet Summer School on Machine Learning and Knowledge Acquisition: LEARNING AND PROBABILITIES – Wray Buntine
4 Data Selection and Model Combination in Connectionist Speech Recognition – Gary David Cook - 1997
563 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
124 Learning dynamic Bayesian networks – Zoubin Ghahramani - 1998
67 Graphical models and automatic speech recognition – Jeffrey A. Bilmes - 2003
16 A Syllable, Articulatory-Feature, and Stress-Accent Model of Speech Recognition – Shuangyu Chang - 2002
3 Bayesian Radial Basis Functions of Unknown Dimension – C.C. Holmes, B.K. Mallick - 1997
1 Bayesian Multioutput Feedforward Neural Network Comparison: A Conjugate Prior Approach – Vivien Rossi, Jean-Pierre Vila
3 Bayesian inverse quantum theory – Jörg C. Lemm, Joerg Uhlig
19 An Anytime Approach To Connectionist Theory Refinement: Refining The Topologies Of Knowledge-Based Neural Networks – David William Opitz - 1995
2 Neural Networks: A Pattern Recognition Perspective – Christopher M. Bishop - 1996
5 Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians – Alberto Ruiz, M. Carmen Garrido - 1998
2 Programming Abstractions in C – Peter Sykacek, Stephen Roberts - 1997
4 How to Implement A Priori Information: A Statistical Mechanics Approach – Jörg C. Lemm - 1998
2 Biologically Inspired Modular Neural Networks – Farooq Azam - 2000
Aspects of the Interface between STatistics and . . . – Matt Whiley - 1999