## Home > Tags: bayesian (Total 29 Records)

### Learning Bayesian Models with R

Programming By:Dr. Hari M. Koduvely 2015-00-00 00:00:00

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems Understand the principles of Bayesian Inference with less mathematical equations Learn state-of-the art Machine Learning methods Familiarize yourself with the recent advances in Dee bayesian machine learning, bayesian linear regression, machine learning methods, bayesian logistic regression, perform bayesian inference

### Advanced Methodologies for Bayesian Networks: Second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings (Lecture Notes in Computer Science)

Computer Science By:Joe Suzuki and Maomi Ueno 2016-02-15 00:00:00

This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerou bayesian networks, international workshop, advanced methodologies, lecture notes, graphical models

Tags:
*computer*
*network*
*lecture*
*science*
*methodology*
*proceedings*
*bayesian*
*ambn*
*yokohama*

### Bayesian Natural Language Semantics and Pragmatics (Language, Cognition, and Mind)

Computer Science By:Henk Zeevat and Hans-Christian Schmitz 2015-06-19 00:00:00

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make prop natural language semantics, bayesian natural language, natural language interpretation, bayesian interpretation, causal bayesian models

Tags:
*language*
*cognition*
*natural*
*pragmatics*
*semantics*
*mind*
*bayesian*

### Innovations in Bayesian Networks: Theory and Applications (Studies in Computational Intelligence)

Programming By:Dawn E. Holmes 2008-11-17 00:00:00

Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained. Both bayesian networks, rapidly growing areas, computational intelligence, prestigious researchers, useful sourcebook

Tags:
*study*
*network*
*application*
*theory*
*computational*
*intelligence*
*innovations*
*bayesian*

### Bayesian Programming

Programming By:Pierre Bessiere 2013-12-20 00:00:00

Probability as an Alternative to Boolean Logic While logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to e bayesian programming, bayesian inference, bayesian inference algorithms, efficient bayesian inference, bayesian programs

Tags:
*programming*
*bayesian*

### Bayesian Inference: with ecological applications

Computers (Other) By:William A Link 2009-08-18 00:00:00

This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context. The advent of fast bayesian inference, prevalent bayesian approach, wildlife biologists, fast personal computers, companion website

### Bayesian Networks: An Introduction

Algorithms By:Timo Koski 2009-11-02 00:00:00

Bayesian Networks: An Introduction provides a selfâ€“contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in clas bayesian networks, complex data sets, conditional gaussian distributions, introductionbayesian networks, dirichlet distribution

### Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation)

Programming By:Nikolay Nikolaev 2006-05-03 00:00:00

This book delivers theoretical and practical knowledge for developing algorithms that infer linear and non-linear multivariate models, providing a methodology for inductive learning of polynomial neural network models (PNN) from data. The text emphasizes an organized model identification process by polynomial neural network, polynomial networks, non-linear multivariate models, computation)this book delivers theoretical and practical knowledge for developing algorithms that infer linear and non-linear multivariate models, providing a methodology for inductive learning of polynomial neural netw

Tags:
*network*
*programming*
*computation*
*learning*
*method*
*genetic*
*bayesian*
*polynomial*

### Bayesian Essentials with R

Programming By:Jean-Michel Marin, Christian Robert 2013-00-00 00:00:00

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian bayesian modeling book, bayesian statistics, computational bayesian statistics, bayesian essentials, bayesian statistics.bayesian essentials

Tags:
*essentials*
*bayesian*

### Bayesian Programming

Algorithms By:Pierre Bessiere 2013-12-20 00:00:00

Probability as an Alternative to Boolean Logic While logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to e bayesian programming, bayesian inference, bayesian programming probability, bayesian inference algorithms, bayesian inference engine

Tags:
*programming*
*bayesian*