Logo

Bayesian Field Theory by J. C. Lemm

Large book cover: Bayesian Field Theory

Bayesian Field Theory
by

Publisher: arXiv.org
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.

Home page url

Download or read it online for free here:
Download link
(1.7MB, PDF)

Similar books

Book cover: An Introduction to Stochastic PDEsAn Introduction to Stochastic PDEs
by - arXiv
This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.
(9083 views)
Book cover: Markov Chains and Stochastic StabilityMarkov Chains and Stochastic Stability
by - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
(16285 views)
Book cover: Seeing Theory: A visual introduction to probability and statisticsSeeing Theory: A visual introduction to probability and statistics
by - Brown University
The intent of the website and these notes is to provide an intuitive supplement to an introductory level probability and statistics course. The level is also aimed at students who are returning to the subject and would like a concise refresher ...
(1720 views)
Book cover: Probability and Statistics: A Course for Physicists and EngineersProbability and Statistics: A Course for Physicists and Engineers
by - De Gruyter Open
This is an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing. Designed for students in engineering and physics.
(307 views)