**Bayesian Field Theory**

by J. C. Lemm

**Publisher**: arXiv.org 2000**Number of pages**: 200

**Description**:

Bayesian field theory denotes a nonparametric Bayesian approach for learning functions from observational data. Based on the principles of Bayesian statistics, a particular Bayesian field theory is defined by combining two models: a likelihood model, providing a probabilistic description of the measurement process, and a prior model, providing the information necessary to generalize from training to non-training data.

Download or read it online for free here:

**Download link**

(1.7MB, PDF)

## Similar books

**Stochastic Integration and Stochastic Differential Equations**

by

**Klaus Bichteler**-

**University of Texas**

Written for graduate students of mathematics, physics, electrical engineering, and finance. The students are expected to know the basics of point set topology up to Tychonoff's theorem, general integration theory, and some functional analysis.

(

**9108**views)

**Principles of Data Analysis**

by

**Cappella Archive**-

**Prasenjit Saha**

This is a short book about the principles of data analysis. The emphasis is on why things are done rather than on exactly how to do them. If you already know something about the subject, then working through this book will deepen your understanding.

(

**8755**views)

**Probability and Statistics Cookbook**

by

**Matthias Vallentin**

The cookbook contains a succinct representation of various topics in probability theory and statistics. It provides a comprehensive reference reduced to the mathematical essence, rather than aiming for elaborate explanations.

(

**13050**views)

**Introduction to Probability, Statistics, and Random Processes**

by

**Hossein Pishro-Nik**-

**Kappa Research, LLC**

This book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, sciences, finance, and other fields. It provides a clear and intuitive approach to these topics.

(

**4667**views)