Results 171 to 180 of about 10,915 (210)
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Application of Maxent to Inverse Photoemission Spectroscopy
1996Information about the spectral density gained by inverse photoemission spectroscopy is distorted by the Fermi distribution and the apparatus function. In many cases recovery of the desired physical quantities is hampered by an ill-posed inversion problem.
Linden, W., Donath, M., Dose, V.
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Maxent-Nesom in Equilibrium Conditions
2002Let us consider a many-body system (the sample in a given experiment) in contact with ideal reservoirs, and, to be specific, let us take the case of thermal and particle reservoirs.
Roberto Luzzi +2 more
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Abbreviation Recognition with MaxEnt Model
2006Abbreviated words carry critical information in the literature of many special domains. This paper reports our research in recognizing dotted abbreviations with MaxEnt model. The key points in our work include: (1) allowing the model to optimize with as many features as possible to capture the text characteristics of context words, and (2) utilizing ...
Chunyu Kit +2 more
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Maxent, Mathematics, and Information Theory
1996This is a mathematically oriented survey about the method of maximum entropy or minimum I-divergence, with a critical treatment of its various justifications and relation to Bayesian statistics. Information theoretic ideas are given substantial attention, including “information geometry”.
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Maxent Applied To Linear Regression
1990Given sparse, unreplicated data of poor instrumental resolution, we determine the probability of linear models using orthogonal least squares regression and MAXENT with an ‘expert draftsman’ constraint. An information bound condition enables MAXENT inference for the reliability of evidence determining the probability distribution for observations of a ...
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Quantified Maxent: An NMR Application
1990‘Classic MaxEnt’ is a Bayesian derivation of the MaxEnt treatment of inverse problems leading to a posterior probability ‘bubble’ over the solution. This probability bubble—which is maximised at the optimal regularised solution—provides the framework for quantitative inferences about the solution.
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