Maximum Entropy and Bayesian Methods

Maximum Entropy and Bayesian Methods

 

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Editorial:
Springer Nature B.V.
Año de edición:
1996
Materia
Probabilidad y estadística
ISBN:
9780792343110

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Preface. Reconstruction f the Probability Density Function Implicit in Option Prices from Incomplete and Noisy Data; R.J. Hawkins, et al. Model Selection and Parameter Estimation for Exponential Signals; A. Ramaswami, G.L. Bretthorst. Hierarchical Bayesian Time-Series Models; L.M. Berliner. Bayesian Time Series: Models and Computations for the Analysis of Time Series in the Physical Sciences; M. West. Maxent, Mathematics, and Information Theory; I. Csiszár. Bayesian Estimation of the Von Mises Concentration Parameter; D.L. Dowe, et al. A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks; D. Geiger, D. Heckerman. The Bootstrap is Inconsistent with Probability Theory; D.H. Wolpert. Data-Driven Priors for Hyperparameters in Regularization; D. Keren, M. Werman. Mixture Modeling to Incorporate Meaningful Constraints into Learning; I. Tchoumatchenko, J.-G. Ganascia. Maximum Entropy (Maxent) Method in Expert Systems and Intelligent Control: New Possibilities and Limitations; V. Kreinovich, et al. The De Finetti Transform; S.J. Press. Continuum Models for Bayesian Image Matching; J.C. Gee, P.D. Peralta. Mechanical Models as Priors in Bayesian Tomographic Reconstruction; A. Rangarajan, et al. The Bayes Inference Engine; K.M. Hanson, G.S. Cunningham. A Full Bayesian Approach for Inverse Problems; A. Mohammad- Djafari. Pixon-Based Multiresolution Image Reconstruction and Quantification of Image Information Content; R.C. Puetter. Bayesian Multimodal Evidence Computation by Adaptive Tempering MCMC; M.-D. Wu, W.J. Fitzgerald. Bayesian Inference and the Analytic Continuation of Imaginary- Time Quantum Monte Carlo Data; J.E. Gubermatis, et al. Spectral Properties from Quantum Monte CarloData: A Consistent Approach; R. Preuss, et al. An Application of Maximum Entropy Method to Dynamical Correlation Functions at Zero Temperature; H. Pang, et al. Chebyshev Moment Problems: Maximum Entropy and Kernel Polynomial Methods; R.N. Silver, et al. Cluster Expansions and Iterative Scaling for Maximum-Entropy Language Models; J.D. Lafferty, B. Suhm. A Maxent Tomography Method for Estimating Fish Densities in a Commercial Fishery; S. Lizamore, et al. Toward Optimal Observer Performance of Detection and Discrimination Tasks on Reconstructions from Sparse Data; R.F. Wagner, et al. Entropies for Dissipative Fluids and Magnetofluids without Discretization; D. Montgomery. On the Importance of &agr; Marginalization in Maximum Entropy; R. Fisher, et al. Quantum Mechanics as an Exotic Probability Theory; S. Youssef. Bayesian Parameter Estimation of Nuclear-Fusion Confinement Time Scaling Laws; V. Dose, et al. Hierarchical Segmentation of Range and Color Images Based on Bayesian Decision Theory; P. Boulanger. Priors on Measures; J. Skilling, S. Sibisi. Determining Whether Two Data Sets are from the Same Distribution; D.H. Wolpert. Occam’s Razor for Parametric Families and Priors on the Space of Distributions; V. Balasubramanian. Skin and Maximum Entropy: A Hidden Complicity? B. Dubertret, et al. Predicting the Accuracy of Bayes Classifiers; R.R. Snapp. Maximum Entropy Analysis of Genetic Algorithms; J.L. Shapiro, et al. Data Fusion in the Field of Non Destructive Testing; S. Gautier, et al. Dual Statistical Mechanical Theory for Unsupervised And Supervised Learning; G. Deco, B. Schürmann. Complex Sinusoid Analysis by Bayesian Deconvolution of the Discrete Fourier Transform; F. Dublanchet, et al. Statistical Mechanics of Choice; P.S

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