Bayesian Inference for Sparse Generalized Linear Models

Matthias Seeger; Sebastian Gerwinn; Matthias Bethge

doi:10.1007/978-3-540-74958-5_29

ScienceGate Book Chapters

BOOK-CHAPTER

Bayesian Inference for Sparse Generalized Linear Models

Matthias Seeger Sebastian Gerwinn Matthias Bethge

Year: 2007 Lecture notes in computer science Pages: 298-309 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-540-74958-5_29

Get Full-Text PDF Get Analytical Report

Keywords:

Generalized linear model Bayesian inference Expectation propagation Bayesian probability Posterior probability Inference Prior probability Computer science Bayesian linear regression Stability (learning theory) Algorithm Mathematics Artificial intelligence Pattern recognition (psychology) Machine learning Gaussian process

Metrics

Cited By

6.77

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Neural dynamics and brain function

Life Sciences → Neuroscience → Cognitive Neuroscience

Functional Brain Connectivity Studies

Life Sciences → Neuroscience → Cognitive Neuroscience

Blind Source Separation Techniques

Physical Sciences → Computer Science → Signal Processing

Bayesian Inference for Sparse Generalized Linear Models

Metrics

Citation History

Topics

Related Documents

Bayesian inference for generalized linear mixed models

Bayesian inference for generalized linear models for spiking neurons

Semiparametric Bayesian inference on generalized linear measurement error models

Bayesian Generalized Linear Models for Inference About Small Areas

A Unified Bayesian Inference Framework for Generalized Linear Models