Jorg C. Lemm
Hardcover: 432 pages Publisher: The Johns Hopkins University Press (June 6, 2003) Language: English ISBN-10: 0801872200 ISBN-13: 978-0801872204
1 Introduction 3
2 Bayesian framework 9
3 Gaussian prior factors 85
4 Parameterizing likelihoods: Variational methods 167
5 Parameterizing priors: Hyperparameters 187
6 Mixtures of Gaussian prior factors 229
7 Bayesian inverse quantum theory (BIQT) 257
8 Summary 309
A A priori information and a posteriori control 313
B Probability, free energy, energy, information, entropy, and
temperature 323
B.I Statistics and statistical mechanics 323
B.2 Probability 325
B.3 Random variables 326
B.4 Temperature and external fields 330
B.5 Conditional probabilities and disordered systems 339
C Iteration procedures: Learning 345
C.I Numerical solution of stationarity equations 345
C.2 Learning matrices 348
C.3 Initial configurations and kernel methods 357
- Bayesian Field Theory.djvu