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Edwin Thompson Jaynes
A Modern History of Probability Theory
A Brief Overview of Probability Theory in Data Science by Geert
Maximum Entropy: the Universal Method for Inference
UC Berkeley UC Berkeley Electronic Theses and Dissertations
Nature, Science, Bayes' Theorem, and the Whole of Reality
Distribution Transformer Semantics for Bayesian Machine Learning
Report from the Chair by Robert H
Topics in Inference and Modeling in Physics a Dissertation Presented to the Faculty of the Graduate School In
THE ISBA NEWSLETTER Vol
This Is IT: a Primer on Shannon's Entropy and Information
Intelligent Machines in the 21St Century: Automating the Processes of Inference and Inquiry by Kevin H
Samenvatting
Pairwise Maximum-Entropy Models and Their Glauber Dynamics: Bimodality, Bistability, Non-Ergodicity Problems, and Their Elimination Via Inhibition
On Gibbs States of Mechanical Systems with Symme- Tries
Entropy in Urban Systems
Deepdive: a Data Management System for Automatic Knowledge Base Construction
Maximum-Entropy Method Applied to Micro- and Nanolasers
A Link Between Nano-And Classical Thermodynamics: Dissipation
Top View
An Approach to Optimal Discretization of Continuous Real Random Variables with Application to Machine Learning
Bayesian Programming
Chapter 3: Bayesian Cosmostatistics