LEADER 02332nam  2200505z- 450 
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035   $a(CKB)4920000000095241
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/50220
035   $a(oapen)doab50220
035   $a(EXLCZ)994920000000095241
100   $a20202102d2019      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aInformation Geometry
210   $cMDPI - Multidisciplinary Digital Publishing Institute$d2019
215   $a1 online resource (356 p.)
311 08$a3-03897-632-6 
330   $aThis Special Issue of the journal Entropy, titled "Information Geometry I", contains a collection of 17 papers concerning the foundations and applications of information geometry. Based on a geometrical interpretation of probability, information geometry has become a rich mathematical field employing the methods of differential geometry. It has numerous applications to data science, physics, and neuroscience. Presenting original research, yet written in an accessible, tutorial style, this collection of papers will be useful for scientists who are new to the field, while providing an excellent reference for the more experienced researcher. Several papers are written by authorities in the field, and topics cover the foundations of information geometry, as well as applications to statistics, Bayesian inference, machine learning, complex systems, physics, and neuroscience.
610   $a?)
610   $a(?
610   $aBezout matrix
610   $adecomposable divergence
610   $adually flat structure
610   $aentropy
610   $aFisher information
610   $aFisher information matrix
610   $ainformation geometry
610   $ainformation theory
610   $aMarkov random fields
610   $amatrix resultant
610   $amaximum pseudo-likelihood estimation
610   $astationary process
610   $aStein equation
610   $aSylvester matrix
610   $atensor Sylvester matrix
610   $aVandermonde matrix
700   $aVerdoolaege$b Geert$4auth$01309762
906   $aBOOK
912   $a9910346839903321
996   $aInformation Geometry$93029571
997   $aUNINA