DiV MaxEnt

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  • Cox, R. T. Probability, Frequency and Reasonable Expectation American Journal of Physics, Volume 14, Issue 1, pp. 1-13 (1946)
  • Alfréd Rényi, On Measures of Entropy and Information Proc. Fourth Berkeley Symp. on Math. Statist. and Prob., Vol. 1 (Univ. of Calif. Press, 1961), 547-561.
  • CLAUDE E. SHANNON, Communication in the Presence of Noise, PROCEEDINGS OF THE IEEE, VOL. 86, NO. 2, FEBRUARY 1998 447
  • Jaynes, E. T., The Minimum Entropy Production Principle, Ann. Rev. Phys. Chem. 31, 579, 1980
  • Jaynes, E. T., Macroscopic Prediction, in Complex Systems - Operational Approaches, H. Haken (ed.), Springer-Verlag, Berlin, p. 254, 1985
  • Jaynes, E. T., Probability in Quantum Theory, in Complexity, Entropy, and the Physics of Information, W. H. Zurek (ed.), Addison-Wesley, Redwood City, CA, p. 381, 1990
  • Ariel Caticha, From Inference to Physics, Presented at MaxEnt 2008, the 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (July 8-13, 2008, Boraceia Beach, Sao Paulo, Brazil)
  • Ariel Caticha, Entropic Dynamics, Presented at MaxEnt 2001, the 21th International Workshop on Bayesian Inference and Maximum Entropy Methods (August 4-9, 2001, Baltimore, MD, USA)
  • Ariel Caticha, Updating Probabilities, Presented at MaxEnt 2006, the 26th International Workshop on Bayesian Inference and Maximum Entropy Methods (July 8-13, 2006, Paris, France)
  • Ariel Caticha, Relative Entropy and Inductive Inference, Presented at MaxEnt23, the 23rd International Workshop on Bayesian Inference and Maximum Entropy Methods (August 3-8, 2003, Jackson Hole, WY, USA)
  • Skilling, John, The Canvas of Rationality, BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: Proceedings of the 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP Conference Proceedings, Volume 1073, pp. 67-79 (2008).
  • Sýkora, Stanislav, Quantum theory and the bayesian inference problems, Journal of Statistical Physics, Volume 11, Issue 1, pp.17-27
  • Shore, J., Johnson, R. Axiomatic Derivation of the Principle of Maximum Entropy and the Principle of Minimum Cross-Entropy

IEEE TRANSACTlIONS ON lNFORMATION THEORY, VOL. m26, NO. 1, JANUARY 1980

  • Shore, J., Johnson, R. Properties of cross-entropy minimization 0018-9448/81/0700-0472$00.75 1981 IEEE
  • Kevin H. Knuth, John Skilling, Foundations of Inference, Axioms 2012, 1(1):38-73
  • Kevin H. Knuth, The Origin of Probability and Entropy, Bayesian inference and Maximum Entropy Methods in Science and Engineering, Sao Paulo, Brazil, 2008
  • Y. Tikochinsky, Feynman Rules for Probability Amplitudes, International Journal of Theoretical Physics, Vol. 27, No. 5, 1988
  • Y. Tikochinsky*, N. Z. Tishby*, and R. D. Levine ,Consistent Inference of Probabilities for Reproducible Experiments, Phys. Rev. Lett. 52, 1357–J. M. Borwein, A. S. Lewis and D. Noll1360 (1984)
  • P. Ván Unique additive information measures - Boltzmann-Gibbs-Shannon, Fisher and beyond Physica A, 2006, V365, p28-33
  • Jos Uffink, The Constraint Rule of the Maximum Entropy Principle, Studies of the History and Philosophy of Modern Physics, 27, 47-49, 1996
  • Jos Uffink, Can the Maximum Entropy Principle Be Explained as a Consistency Requirement?, Stud.Hist.Phil.Mod.Phys. 26, 223-261, 1995
  • Tommaso Toffoli, How much of physics is just computation?, Superlattices and Microstructures, 23, 381-406 (1998)
  • Tommaso Toffoli, Action, Or the Fungibility of Computation, Feynman and Computation, 349-392 (1999)
  • Tommaso Toffoli, Occam, Turing, von Neumann, Jaynes: How much can you get for how little?, proceedings of the conference ACRI '94: Automi Cellulari per la Ricerca e l'Industria, Rende (CS), Italy, September 29--30, 1994
  • Plastino, A.; Plastino, A. R., On the universality of thermodynamics' Legendre transform structure, Physics Letters A 226 (1997) 257-263
  • A. Plastino, E. M. F. Curado, Equivalence between maximum entropy principle and enforcing dU=TdS, Phys. Rev. E 72, 047103 (2005)
  • A. Plastino, A. R. Plastino, B H Soffer, Fisher information and thermodynamics' 1st. law, arXiv:cond- mat/0509697 v2 28 Sep 2005
  • F. Pennini, A. Plastino, Heisenberg-Fisher thermal uncertainty measure, Phys. Rev. E 69, 057101 (2004)
  • F. Pennini and A. Plastino, Reciprocity relations between ordinary temperature and the Frieden-Soffer Fisher temperature, Phys. Rev. E 71, 047102 (2005)
  • A. Hernando, A. Plastino, A. R. Plastino, MaxEnt and dynamical information, arXiv:1201.0889v1 [physics.data-an] 4 Jan 2012
  • Michael E. Fisher Solution of a Combinatorial Problem—Intermediate Statistics American Journal of Physics -- January 1962 -- Volume 30, Issue 1, pp. 49
  • B. Roy Frieden and Bernard H. Soffer Lagrangians of physics and the game of Fisher-information transfer Phys. Rev. E 52, 6917–6917 (1995)
  • Humphrey J. Maris and Leo P. Kadanoff Teaching the renormalization group American Journal of Physics -- June 1978 -- Volume 46, Issue 6, pp. 652
  • W. K. Wootters Statistical distance and Hilbert space Phys. Rev. D 23, 357–362 (1981)
  • Kurt Wiesenfeld Resource Letter: ScL-1: Scaling laws American Journal of Physics -- September 2001 -- Volume 69, Issue 9, pp. 938
  • V Dose Bayesian inference in physics: case studies 2003 Rep. Prog. Phys. 66 1421
  • Anand G. Dabak , Don H. Johnson Relations between Kullback-Leibler distance and Fisher information (2002)

unfolding

  • E.T. jaynes Prior information and ambiguity in inverse problem SIAM-AMS Proceeding V14 1984
  • S.F. Gull and J. Skilling, Maximum Entropy Image Reconstruction: General Algorithm, Monthly Notices of the Royal Astronomical Society, Vol. 211, NO.1, P. 111, 1984
  • S.F. Gull and J. Skilling, Maximum entropy method in image processing', IEE PROCEEDINGS, Vol. 131, Pt. F, No. 6, OCTOBER 1984
  • J. M. Borwein, A. S. Lewis and D. Noll Maximum Entropy Reconstruction Using Derivative Information, Part 1: Fisher Information and Convex Duality
  • J. M. Borwein , A. S. Lewis , M. N. Limber , D. Noll Maximum Entropy Spectral Analysis Using Derivative Information Part 2: Computational Results
  • FRÖHNER F. H. Assigning uncertainties to scientific data
  • K. Zarb Adami Variational Methods in Bayesian Deconvolution PHYSTAT2003, SLAC, Stanford, California, September 8-11, 2003
  • Marcel Reginattoa, Paul Goldhagena, Sonja Neumannb, Spectrum unfolding, sensitivity analysis and propagation of uncertainties with the maximum entropy deconvolution code MAXED Nuclear Instruments and Methods in Physics Research Section A, Volume 476, Issues 1–2, 1 January 2002, Pages 242–246
  • G. D'Agostini Improved iterative Bayesian unfolding arXiv:1010.0632v1 [physics.data-an] 4 Oct 2010
  • A. Mohammad-Djafari, Jérôme Idier A scale invariant Bayesian method to solve linear inverse problems arXiv:physics/0111125v1 [physics.data-an] 14 Nov 2001
  • Shikoh ITOH & Toshiharu TSUNODA Neutron Spectra Unfolding with Maximum Entropy and Maximum Likelihood Journal of Nuclear Science and Technology Volume 26, Issue 9, 1989
  • Yuan Qi, Thomas P. Minka, and Rosalind W. Picard Bayesian Spectrum Estimation of Unevenly Sampled Nonstationary Data EDICS: 2-TIFR, 2-SPEC
  • Aristidis C. Likas and Nikolas P. Galatsanos A Variational Approach for Bayesian Blind Image Deconvolution 2222 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 52, NO. 8, AUGUST 2004
  • U. Gerhardt, S. Marquardt, N. Schroeder, S. Weiss Bayesian deconvolution and analysis of photoelectron or any other spectra: Fermi-liquid versus marginal Fermi-liquid behavior of the 3d electrons in Ni Phys. Rev. B » Volume 58 » Issue 11
  • Jose M. Bioucas-Dias, Mario A. T. Figueiredo, and Joao P. Oliveira ADAPTIVE TOTAL VARIATION IMAGE DECONVOLUTION: A MAJORIZATION-MINIMIZATION APPROACH
  • Satoh, T., Matsui, A., Hirohata, T., Matsumoto, T. A hierarchical Bayesian deconvolution with positivity constraints 0-7803-5871-6/99/$10.00 1999 IEEE
  • Georgios Choudalakis Fully Bayesian Unfolding

Bayesian Folder

  • H. M. Franca, A. Maia, Jr., and C. P. Malta Maxwell Electromagnetic Theory, Planck's Radiation Law, and Bose-Einstein Statistics Foundations ~['Ph.l,.s'ics, 1~,I. 26, No. & 1996
  • J. Aitchison On Coherence in Parametric Density Estimation Vol. 77, No. 4, Dec., 1990 > On Coherence in Para...
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