Maximum Entropy and Bayesian Methods: Boise, Idaho, USA, 1997 Proceedings of the 17th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis: 98 - Rilegato

Erickson, G.; Rychert, Joshua T.; Smith, C. R.

 
9780792350477: Maximum Entropy and Bayesian Methods: Boise, Idaho, USA, 1997 Proceedings of the 17th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis: 98

Sinossi

This volume contains a wide range of applications from Bayesian statistics and maximum entropy methods to problems of concern in such fields as image processing, coding theory, machine learning, economics, data analysis and various other problems. It is a compendium of papers by the leading researchers in the field of Bayesian statistics and maximum entropy methods and represents developments in the field. This should be of interest to researchers in applied statistics, information theory, coding theory, image and signal processing.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Contenuti

In Memory of Edwin T. Jaynes. Preface. Massive Inference and Maximum Entropy; J. Skilling. CV-NP Bayesianism by MCMC; C. Rodriguez. Which Algorithms are Feasible? A MAXENT Approach; D.E. Cooke, et al. Maximum Entropy, Likelihood and Uncertainty: A Comparison; A. Golan. Probabilistic Methods for Data Fusion; A. Mohammed-Djafari. Whence the Laws of Probability? A.J.M. Garrett. Bayesian Group Analysis; W. von der Linden, et al. Symmetry-Group Justification of Maximum Entropy Method and Generalized Maximum Entropy Methods in Image Processing; O. Kosheleva. Probability Synthesis, How to Express Probabilities in Terms of Each Other; A.J.M. Garrett. Inversion Based on Computational Simulations; K. Hanson, et al. Model Comparison with Energy Confinement Data From Large Fusion Experiments; R. Preuss, et al. Deconvolution Based on Experimentally Determined Apparatus Functions; V. Dose, et al. A Bayesian Approach for the Determination of the Charge Density from Elastic Electron Scattering Data; A. Mohammad-Djafari, H.G. Miller. Integrated Deformable Boundary Finding Using Bayesian Strategies; A. Chakraborty, J. Duncan. Shape Reconstruction in X-Ray Tomography from a Small Number of Projections Using Deformable Models; A. Mohammad-Djafari, K. Sauer. An Empirical Model of Brain Shape; J. Gee, L. Le Briquer. Difficulties Applying Blind Source Separation Techniques to EEG and MEG; K.H. Knuth. The History of Probability Theory; A.J.M. Garrett. We Must Choose the Simplest Physical Theory: Levin-Li-Vitányi Theorem and Its Potential Physical Applications; D. Fox, et al. Maximum Entropy and Acausal Processes: Astrophysical Applications and Challenges; M. Koshelev. Computational Exploration of the Entropic Prior Over Spaces of Low Dimensionality;H.E. Fitzgerald, E.G. Larson. Environmentally-Oriented Processing of Multi-Spectral Satellite Images: New Challenges for Bayesian Methods; S.A. Starks, V. Kreinovich. Maximum Entropy Approach to Optimal Sensor Placement for Aerospace Non-Destructive Testing; R. Osegueda, et al. Maximum Entropy Under Uncertainty; H. Gzyl. Subject Index.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Altre edizioni note dello stesso titolo

9789401061117: Maximum Entropy and Bayesian Methods: Boise, Idaho, USA, 1997 Proceedings of the 17th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis: 98

Edizione in evidenza

ISBN 10:  9401061114 ISBN 13:  9789401061117
Casa editrice: Springer, 2012
Brossura