Bayesian Methods for Neural Networks (1999)


Download Links

by João F. G. De Freitas
Citations:7 - 0 self

Active Bibliography

12 Robust Full Bayesian Learning for Neural Networks – Christophe Andrieu, Nando de Freitas, Arnaud Doucet - 1999
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
State Estimation of Probabilistic Hybrid Systems with Particle Filters – Stanislav Funiak - 2004
LETTER Communicated by Steven Nowlan and Gerard Dreyfus Sequential Monte Carlo Methods to Train Neural Network Models – J. F. G. De Freitas, M. Niranjan, A. H. Gee, A. Doucet
10 Sequential Monte Carlo Methods For Optimisation Of Neural Network Models – Nando de Freitas, Mahesan Niranjan, Andrew Gee, Arnaud Doucet - 1998
8 Nonparametric Regression for Learning Nonlinear Transformations – Stefan Schaal
1 Hidden Dynamic Models for Speech Processing Applications – Leo Jingyu Lee
66 Constructive Algorithms for Structure Learning in Feedforward Neural Networks for Regression Problems – Tin-yau Kwok, Dit-Yan Yeung - 1997
7 On Bayesian model assessment and choice using cross-validation predictive densities – Aki Vehtari, Jouko Lampinen - 2001
26 Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities – Aki Vehtari, Jouko Lampinen - 2002
199 Using simulation methods for Bayesian econometric models: Inference, development and communication – John Geweke - 1999
24 Robust Full Bayesian Learning for Radial Basis Networks – Christophe Andrieu, Nando de Freitas, Arnaud Doucet - 2001
3 Nonparametric regression for learning – Stefan Schaal - 1994
222 An Introduction to MCMC for Machine Learning – Christophe Andrieu - 2003
2 Dynamic Neural Regression Models – Thomas Briegel, Volker Tresp - 2000
160 Constructive Incremental Learning from Only Local Information – Stefan Schaal, Christopher G. Atkeson - 1998
LETTER Communicated by Michael Jordan Robust Full Bayesian Learning for Radial Basis Networks – Christophe Andrieu, Nando De Freitas, Arnaud Doucet
30 A review of dimension reduction techniques – Miguel Á. Carreira-perpiñán - 1997
Estimation and Inference via Bayesian Simulation: An Introduction to Markov – Chain Monte Carlo, Simon Jackman