Robust full Bayesian learning for radial basis networks.

Robust full Bayesian learning for radial basis networks.

Čájet eará veršuvnnaid (1)

We propose a hierarchical full Bayesian model for radial basis networks. This model treats the model dimension (number of neurons), model parameters, regularization parameters, and noise parameters as unknown random variables. We develop a reversible-jump Markov chain Monte Carlo (MCMC) method to pe...

Bibliográfalaš dieđut
Váldodahkkit:	Andrieu, C, de Freitas, N, Doucet, A
Materiálatiipa:	Journal article
Giella:	English
Almmustuhtton:	2001

Geahča maid

Robust Full Bayesian Learning for Radial Basis Networks
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2001)

Robust full Bayesian methods for neural networks
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2000)

Sequential MCMC for Bayesian model selection
Dahkki: Andrieu, C, et al.
Almmustuhtton: (1999)

Bayesian radial basis functions of variable dimension
Dahkki: Holmes, C, et al.
Almmustuhtton: (1998)

Robust neural network predictors using radial basis functions
Dahkki: Siti Hajar Salleh,
Almmustuhtton: (1998)

Sequential MCMC for Bayesian model selection
Dahkki: Andrieu, C, et al.
Almmustuhtton: (1999)

Computational advances for and from Bayesian analysis
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2004)

Learning in Deep Radial Basis Function Networks
Dahkki: Fabian Wurzberger, et al.
Almmustuhtton: (2024-04-01)

On sequential Monte Carlo sampling methods for Bayesian filtering
Dahkki: Doucet, A, et al.
Almmustuhtton: (2000)

Bayesian deconvolution of noisy filtered point processes
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2001)

Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC
Dahkki: Andrieu, C, et al.
Almmustuhtton: (1999)

An introduction to Monte Carlo methods for Bayesian data analysis
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2001)

An active learning approach for radial basis function neural networks
Dahkki: Abdullah, S. S., et al.
Almmustuhtton: (2006)

Learning Bayesian Networks That Enable Full Propagation of Evidence
Dahkki: Anthony C. Constantinou
Almmustuhtton: (2020-01-01)

Particle methods for Bayesian modeling and enhancement of speech signals
Dahkki: Vermaak, J, et al.
Almmustuhtton: (2002)

Trans-dimensional MCMC for Bayesian policy learning
Dahkki: Hoffman, M, et al.
Almmustuhtton: (2009)

Bayesian Policy Learning with Trans−Dimensional MCMC
Dahkki: Hoffman, M, et al.
Almmustuhtton: (2007)

Rao−Blackwellised Particle Filtering for Dynamic Bayesian Networks
Dahkki: Doucet, A, et al.
Almmustuhtton: (2000)

Robust Position Control of Electro-Hydrostatic Actuator Systems with Radial Basis Function Neural Networks
Dahkki: Jeongju CHOI
Almmustuhtton: (2013-04-01)

Reversible Jump MCMC Simulated Annealing for Neural Networks
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2000)

Radial Basis Function Cascade Correlation Networks
Dahkki: Peter de B. Harrington, et al.
Almmustuhtton: (2009-08-01)

A novel radial basis Bayesian regularization deep neural network for the Maxwell nanofluid applied on the Buongiorno model
Dahkki: Zulqurnain Sabir, et al.
Almmustuhtton: (2023-06-01)

Bayesian curve fitting using MCMC with applications to signal segmentation
Dahkki: Punskaya, E, et al.
Almmustuhtton: (2002)

On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks
Dahkki: L.N.M. Tawfiq, et al.
Almmustuhtton: (2017-05-01)

Adaptive Robust Stability Control of All-Electrical Tank Gun Compensated by Radial Basis Neural Network
Dahkki: Yimin Wang, et al.
Almmustuhtton: (2023-01-01)

Radial basis function neural network learning with modified backpropagation algorithm /
Dahkki: Usman Muhammad Tukur, 1977-, et al.
Almmustuhtton: (2014)

Learning enhancement of radial basis function network with particle swarm optimization /
Dahkki: 441576 Sultan Noman Qasem Mohammed, et al.
Almmustuhtton: (2008)

Reversible jump Markov chain Monte Carlo strategies for Bayesian model selection in autoregressive processes
Dahkki: Vermaak, J, et al.
Almmustuhtton: (2004)

Remaining Useful Life Prediction Based on the Bayesian Regularized Radial Basis Function Neural Network for an External Gear Pump
Dahkki: Rui Guo, et al.
Almmustuhtton: (2020-01-01)

Estimation of Radial Basis Function Network Centers via Information Forces
Dahkki: Edilson Sousa Júnior, et al.
Almmustuhtton: (2022-09-01)

RADIAL BASIS FUNCTION NETWORKS FOR MOBILE ROBOT LOCALIZATION
Dahkki: Townsend, N, et al.
Almmustuhtton: (1994)

Full-Field Strain Determination for Additively Manufactured Parts Using Radial Basis Functions
Dahkki: Stefan Hartmann, et al.
Almmustuhtton: (2021-12-01)

An introduction to MCMC for machine learning
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2003)

An Introduction to MCMC for Machine Learning
Dahkki: Andrieu, C, et al.
Almmustuhtton: (2003)

Robust adaptive nonlinear PID controller using radial basis function neural network for ballbots with external force
Dahkki: Van-Truong Nguyen, et al.
Almmustuhtton: (2025-01-01)

Learning enhancement of radial basis function neural network with harmony search algorithm /
Dahkki: Mohamed Hassan Ahmed, 1970-, et al.
Almmustuhtton: (2013)

Robust Structure Learning of Bayesian Network by Identifying Significant Dependencies
Dahkki: Yuguang Long, et al.
Almmustuhtton: (2019-01-01)

Statistical guarantees for the robustness of Bayesian neural networks
Dahkki: Cardelli, L, et al.
Almmustuhtton: (2019)

SMC Samplers for Bayesian Optimal Nonlinear Design
Dahkki: Kuck, H, et al.
Almmustuhtton: (2006)

Regularized radial basis function networks : theory and applications /
Dahkki: Yee, Paul V., 1966-, et al.
Almmustuhtton: (2001)