The Net Advance of Physics:
BAYESIAN METHODS
BAYESIAN METHODS:
General:
D'Agostini 2003/04;
Topics in statistical data analysis for high-energy physics
by G. Cowan [2009/06]
How to Use Experimental Data to Compute the Probability of Your Theory
by Georgios Choudalakis [2011/10]
Measurement Error Models in Astronomy
by Brandon C. Kelly [2011/06]
Understanding better (some) astronomical data using Bayesian methods
by Stefano Andreon [2011/12]
Frequentism and Bayesianism: A Python-driven Primer
by Jake VanderPlas [2014/11]
Bayesian Statistics in Software Engineering: Practical Guide and Case Studies
by Carlo A. Furia [2016/08]
Three Lectures on Probability and Statistics
by Carlos Mana [2016/10]
To Bayes or not to Bayes? That's no longer the question!
by Ernest Fokoue [2018/05]
A Guide to General-Purpose Approximate Bayesian Computation Software
by Athanasios Kousathanas et al. [2018/06]
Lectures on Statistics in Theory: Prelude to Statistics in Practice
by Robert D. Cousins [2018/07]
An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models
by Eric Thrane and Colm Talbot [2018/09]
Bayesian Regularization: From Tikhonov to Horseshoe
by Nicholas G. Polson and Vadim Sokolov [2019/02]
Introducing Bayesian Analysis with M&Ms: An Active-Learning Exercise for Undergraduates
by Gwendolyn Eadie et al. [2019/04]
A Review of Approximate Bayesian Computation Methods via Density Estimation: Inference for Simulator-Models
by Clara Grazian and Yanan Fan [2019/09]
Bayesian Design of Experiments: Implementation, Validation and Application to Chemical Kinetics
by Eric A. Walker and Kishore Ravisankar [2019/09]
Type: HIERARCHICAL:
One, no one, and one hundred thousand: Inferring the properties of a population in presence of selection effects
by S. Vitale [2020/07]
Type: QUANTUM:
An Introduction to Quantum Bayesian Networks for Mixed States
by Robert R. Tucci [2012/04]
Re: ASTROPHYSICS:
Bayesian Model Averaging in Astrophysics: A Review
by David Parkinson and Andrew R. Liddle [
Statistical Analysis and Data Mining 6
, 3 (2013)]
Bayesian Coronal Seismology
by Iñigo Arregui [2017/09]
Bayesian Methods for Exoplanet Science
by Hannu Parviainen [2017/11]
An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models
by Eric Thrane and Colm Talbot [2018/09]
Re: BIOSCIENCES:
Approximation and inference methods for stochastic biochemical kinetics - a tutorial review
by David Schnoerr et al. [
Journal of Physics A 50
, 093001 (2017)]
Re: COMPUTER SCIENCE:
Naive Bayes and Text Classification I - Introduction and Theory
by Sebastian Raschka [2014/10]
Bayesian Statistics in Software Engineering: Practical Guide and Case Studies
by Carlo A. Furia [2016/08]
Re:
COSMOLOGY:
Bayes in the sky: Bayesian inference and model selection in cosmology
by Roberto Trotta [2008/03]
Bayesian Methods in Cosmology
by Roberto Trotta [2014/03]
Re: FISHER INFORMATION:
A Tutorial on Fisher Information
by Alexander Ly et al. [2017/05]
Re: MARKOV CHAIN MONTE CARLO:
A Conceptual Introduction to Markov Chain Monte Carlo Methods
by Joshua S. Speagle [2019/09]
Re: NEURAL NETWORKS:
Bayesian neural networks
by T. Charnock et al. [2020/06]
Re: OPTIMISATION:
A Tutorial on Bayesian Optimization
by Peter I. Frazier [2018/07]
THE NET ADVANCE OF PHYSICS