Results 271 to 280 of about 1,600,993 (289)
Efficient and dynamic neural geometry of value and modality encoding in the primate putamen for value-guided behavior. [PDF]
Nat CommunHwang SH, Lee JW, Kim SP, Kim HF.
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Geometry-Dependent Suppression of Quantum Interference in Thiolate- and Nitrile-Terminated Naphthalene Junctions. [PDF]
ACS OmegaYamane A, Fujii S, Nishino T.
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Physics-Embedded Machine Learning Model for Phase Equilibrium Prediction in Multicomponent Systems. [PDF]
J Chem Inf ModelYang Y, Lin ST.
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Coordination Geometry Tuning in a Single-Atom Nanozyme to Mimic Metalloenzymes with Nonplanar Active Site. [PDF]
Adv Sci (Weinh)Lee H +5 more
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Japanese Journal of Mathematics, 2021
SummaryStatistical inference is constructed upon a statistical model consisting of a parameterised family of probability distributions, which forms a manifold. It is important to study the geometry of the manifold. It was Professor C. R. Rao who initiated information geometry in his monumental paper published in 1945.
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SummaryStatistical inference is constructed upon a statistical model consisting of a parameterised family of probability distributions, which forms a manifold. It is important to study the geometry of the manifold. It was Professor C. R. Rao who initiated information geometry in his monumental paper published in 1945.
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2017
This chapter investigates probability distributions on a finite sample space and takes advantage of the more elementary nature of this setting. There are two complementary ways to view a probability distribution. One consists in viewing it as (positive) measure with total mass 1.
Hông Vân Lê +3 more
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This chapter investigates probability distributions on a finite sample space and takes advantage of the more elementary nature of this setting. There are two complementary ways to view a probability distribution. One consists in viewing it as (positive) measure with total mass 1.
Hông Vân Lê +3 more
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Information Geometry and Statistics
2017We apply the functional analytical and differential geometric results of the preceding chapters to the field of statistics and obtain very general versions of the basic classical results. In a narrower sense, the term statistic refers to a mapping from a given sample space Ω to another Ω′, and it is called sufficient for a parametric family, if the ...
Jürgen Jost +3 more
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Informational geometry of social choice [PDF]
Social Choice and Welfare, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Information geometry of Boltzmann machines [PDF]
IEEE Transactions on Neural Networks, 1992 A Boltzmann machine is a network of stochastic neurons. The set of all the Boltzmann machines with a fixed topology forms a geometric manifold of high dimension, where modifiable synaptic weights of connections play the role of a coordinate system to specify networks. A learning trajectory, for example, is a curve in this manifold.
H. Nagaoka, Shun-ichi Amari, K. Kurata
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A foundation of information geometry [PDF]
Electronics and Communications in Japan (Part I: Communications), 1983 AbstractThis paper proposes a new geometrical basic theory for the field of information science. the traditional theory for the information system is occupied fully by detailed discussions of the properties of a system, and the importance has not been recognized for the mutual relationship within a set of information systems.
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