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1.
Probabilisticpossibilistic belief networks
Open Access
Title:
Probabilisticpossibilistic belief networks
Author:
Marco E. G. V. Cattaneo
;
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
;
Marco E. G. V. Cattaneo
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The interpretation of membership functions of fuzzy sets as statistical likelihood functions leads to a probabilisticpossibilistic hierarchical description of uncertain knowledge. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the dat...
The interpretation of membership functions of fuzzy sets as statistical likelihood functions leads to a probabilisticpossibilistic hierarchical description of uncertain knowledge. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the data. This paper studies the possibility of using fuzzy probabilities to describe the uncertain knowledge about the values of the nodes of belief networks. 1
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The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20130818
Source:
http://epub.ub.unimuenchen.de/4448/1/report.pdf
http://epub.ub.unimuenchen.de/4448/1/report.pdf
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Document Type:
text
Language:
en
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Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.3145
http://epub.ub.unimuenchen.de/4448/1/report.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.3145
http://epub.ub.unimuenchen.de/4448/1/report.pdf
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2.
http://www.stat.unimuenchen.de ProbabilisticPossibilistic Belief Networks
Open Access
Title:
http://www.stat.unimuenchen.de ProbabilisticPossibilistic Belief Networks
Author:
Marco E. G. V. Cattaneo
;
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
;
Marco E. G. V. Cattaneo
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Description:
The interpretation of membership functions of fuzzy sets as statistical likelihood functions leads to a probabilisticpossibilistic hierarchical description of uncertain knowledge. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the dat...
The interpretation of membership functions of fuzzy sets as statistical likelihood functions leads to a probabilisticpossibilistic hierarchical description of uncertain knowledge. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the data. This paper studies the possibility of using fuzzy probabilities to describe the uncertain knowledge about the values of the nodes of belief networks. 1
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Year of Publication:
20100924
Source:
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/lmu32.pdf
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/lmu32.pdf
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en
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.172.5958
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/lmu32.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.172.5958
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/lmu32.pdf
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3.
Probabilisticpossibilistic belief networks
Open Access
Title:
Probabilisticpossibilistic belief networks
Author:
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
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Description:
Abstract: The interpretation of membership functions of fuzzy sets as statistical likelihood functions leads to a probabilisticpossibilistic hierarchical description of uncertain knowledge. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided ...
Abstract: The interpretation of membership functions of fuzzy sets as statistical likelihood functions leads to a probabilisticpossibilistic hierarchical description of uncertain knowledge. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the data. This paper studies the possibility of using fuzzy probabilities to describe the uncertain knowledge about the values of the nodes of belief networks. 1
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Year of Publication:
20110508
Source:
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/vsim09.pdf
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/vsim09.pdf
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en
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.6528
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/vsim09.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.6528
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/vsim09.pdf
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4.
7th International Symposium on Imprecise Probability: Theories and Applications, Innsbruck, Austria, 2011 Regression with Imprecise Data: A Robust Approach
Open Access
Title:
7th International Symposium on Imprecise Probability: Theories and Applications, Innsbruck, Austria, 2011 Regression with Imprecise Data: A Robust Approach
Author:
Marco E. G. V. Cattaneo
;
Andrea Wiencierz
Marco E. G. V. Cattaneo
;
Andrea Wiencierz
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Description:
We introduce a robust regression method for imprecise data, and apply it to social survey data. Our method combines nonparametric likelihood inference with imprecise probability, so that only very weak assumptions are needed and different kinds of uncertainty can be taken into account. The proposed regression method is based on interval dominanc...
We introduce a robust regression method for imprecise data, and apply it to social survey data. Our method combines nonparametric likelihood inference with imprecise probability, so that only very weak assumptions are needed and different kinds of uncertainty can be taken into account. The proposed regression method is based on interval dominance: interval estimates of quantiles of the error distribution are used to identify plausible descriptions of the relationship of interest. In the application to social survey data, the resulting set of plausible descriptions is relatively large, reflecting the amount of uncertainty inherent in the analyzed data set.
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Year of Publication:
20120525
Source:
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/isipta112.pdf
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/isipta112.pdf
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Document Type:
text
Language:
en
Subjects:
imprecise data
imprecise data
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.229.3957
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/isipta112.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.229.3957
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/isipta112.pdf
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5.
On the Robustness of Imprecise Probability Methods
Open Access
Title:
On the Robustness of Imprecise Probability Methods
Author:
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
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Imprecise probability methods are often claimed to be robust, or more robust than conventional methods. In particular, the higher robustness of the resulting methods seems to be the principal argument supporting the imprecise probability approach to statistics over the Bayesian one. The goal of the present paper is to investigate the robustness ...
Imprecise probability methods are often claimed to be robust, or more robust than conventional methods. In particular, the higher robustness of the resulting methods seems to be the principal argument supporting the imprecise probability approach to statistics over the Bayesian one. The goal of the present paper is to investigate the robustness of imprecise probability methods, and in particular to clarify the terminology used to describe this fundamental issue of the imprecise probability approach.
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Year of Publication:
20140306
Source:
http://www.stat.unimuenchen.de/~
cattaneo
/publications/isipta13.pdf
http://www.stat.unimuenchen.de/~
cattaneo
/publications/isipta13.pdf
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Document Type:
text
Language:
en
Subjects:
sensitivity analysis ; imprecise
sensitivity analysis ; imprecise
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.357.9797
http://www.stat.unimuenchen.de/~cattaneo/publications/isipta13.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.357.9797
http://www.stat.unimuenchen.de/~cattaneo/publications/isipta13.pdf
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6.
Likelihoodbased inference for probabilistic graphical models: Some preliminary results
Open Access
Title:
Likelihoodbased inference for probabilistic graphical models: Some preliminary results
Author:
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
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A method for calculating some profile likelihood inferences in probabilistic graphical models is presented and applied to the problem of classification. It can also be interpreted as a method for obtaining inferences from hierarchical networks, a kind of imprecise probabilistic graphical models. 1
A method for calculating some profile likelihood inferences in probabilistic graphical models is presented and applied to the problem of classification. It can also be interpreted as a method for obtaining inferences from hierarchical networks, a kind of imprecise probabilistic graphical models. 1
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Year of Publication:
20110508
Source:
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/pgm10.pdf
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/pgm10.pdf
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text
Language:
en
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.7363
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/pgm10.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.7363
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/pgm10.pdf
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7.
7th International Symposium on Imprecise Probability: Theories and Applications, Innsbruck, Austria, 2011 LikelihoodBased Naive Credal Classifier
Open Access
Title:
7th International Symposium on Imprecise Probability: Theories and Applications, Innsbruck, Austria, 2011 LikelihoodBased Naive Credal Classifier
Author:
Alessandro Antonucci
;
Marco E. G. V. Cattaneo
;
Giorgio Corani
Alessandro Antonucci
;
Marco E. G. V. Cattaneo
;
Giorgio Corani
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Description:
The naive credal classifier extends the classical naive Bayes classifier to imprecise probabilities, substituting the imprecise Dirichlet model for the uniform prior. As an alternative to the naive credal classifier, we present a likelihoodbased approach, which extends in a novel way the naive Bayes towards imprecise probabilities, by consideri...
The naive credal classifier extends the classical naive Bayes classifier to imprecise probabilities, substituting the imprecise Dirichlet model for the uniform prior. As an alternative to the naive credal classifier, we present a likelihoodbased approach, which extends in a novel way the naive Bayes towards imprecise probabilities, by considering any possible quantification (each one defining a naive Bayes classifier) apart from those assigning to the available data a probability below a given threshold level. Besides the available supervised data, in the likelihood evaluation we also consider the instance to be classified, for which the value of the class variable is assumed missingatrandom. We obtain a closed formula to compute the dominance according to the maximality criterion for any threshold level. As there are currently no wellestablished metrics for comparing credal classifiers which have considerably different determinacy, we compare the two classifiers when they have comparable determinacy, finding that in those cases they generate almost equivalent classifications.
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Year of Publication:
20120507
Source:
http://www.idsia.ch/%7Egiorgio/pdf/isipta11likelihood.pdf
http://www.idsia.ch/%7Egiorgio/pdf/isipta11likelihood.pdf
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Document Type:
text
Language:
en
Subjects:
naive credal classifier
naive credal classifier
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DDC:
519 Probabilities & applied mathematics
(computed)
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.2487
http://www.idsia.ch/%7Egiorgio/pdf/isipta11likelihood.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.2487
http://www.idsia.ch/%7Egiorgio/pdf/isipta11likelihood.pdf
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8.
Fuzzy probabilities based on the likelihood function. In Soft Methods for Handling Variability and Imprecision
Open Access
Title:
Fuzzy probabilities based on the likelihood function. In Soft Methods for Handling Variability and Imprecision
Author:
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
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Abstract If we interpret the statistical likelihood function as a measure of the relative plausibility of the probabilistic models considered, then we obtain a hierarchical description of uncertain knowledge, offering a unified approach to the combination of probabilistic and possibilistic uncertainty. The fundamental advantage of the resulting ...
Abstract If we interpret the statistical likelihood function as a measure of the relative plausibility of the probabilistic models considered, then we obtain a hierarchical description of uncertain knowledge, offering a unified approach to the combination of probabilistic and possibilistic uncertainty. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the data. Key words: likelihood function, hierarchical model, fuzzy probabilities, imprecise probabilities, statistical inconsistency 1
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Springer
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Year of Publication:
20130717
Source:
http://www.stat.unimuenchen.de/~
cattaneo
/publications/smps08uv.pdf
http://www.stat.unimuenchen.de/~
cattaneo
/publications/smps08uv.pdf
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en
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.3047
http://www.stat.unimuenchen.de/~cattaneo/publications/smps08uv.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.3047
http://www.stat.unimuenchen.de/~cattaneo/publications/smps08uv.pdf
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9.
Foundations of Probability
Open Access
Title:
Foundations of Probability
Author:
Thomas Augustin
;
Marco E. G. V. Cattaneo
Thomas Augustin
;
Marco E. G. V. Cattaneo
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Probability theory is that part of mathematics that is concerned with the description and modeling of random phenomena, or in a more general — but not unanimously accepted — sense, of any kind of uncertainty. Probability is assigned to random events, expressing their tendency to occur in a random experiment, or more generally to propositions, ch...
Probability theory is that part of mathematics that is concerned with the description and modeling of random phenomena, or in a more general — but not unanimously accepted — sense, of any kind of uncertainty. Probability is assigned to random events, expressing their tendency to occur in a random experiment, or more generally to propositions, characterizing the degree of
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20130717
Source:
http://www.stat.unimuenchen.de/~
cattaneo
/publications/iessuv.pdf
http://www.stat.unimuenchen.de/~
cattaneo
/publications/iessuv.pdf
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en
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.3347
http://www.stat.unimuenchen.de/~cattaneo/publications/iessuv.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.3347
http://www.stat.unimuenchen.de/~cattaneo/publications/iessuv.pdf
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10.
Fuzzy probabilities based on the likelihood function. In Soft Methods for Handling Variability and Imprecision
Open Access
Title:
Fuzzy probabilities based on the likelihood function. In Soft Methods for Handling Variability and Imprecision
Author:
Marco E. G. V. Cattaneo
Marco E. G. V. Cattaneo
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Description:
Abstract. If we interpret the statistical likelihood function as a measure of the relative plausibility of the probabilistic models considered, then we obtain a hierarchical description of uncertain knowledge, offering a unified approach to the combination of probabilistic and possibilistic uncertainty. The fundamental advantage of the resulting...
Abstract. If we interpret the statistical likelihood function as a measure of the relative plausibility of the probabilistic models considered, then we obtain a hierarchical description of uncertain knowledge, offering a unified approach to the combination of probabilistic and possibilistic uncertainty. The fundamental advantage of the resulting fuzzy probabilities with respect to imprecise probabilities is the ability of using all the information provided by the data.
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Springer
Contributors:
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Year of Publication:
20100924
Source:
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/smps08.pdf
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/smps08.pdf
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Document Type:
text
Language:
en
Subjects:
Likelihood function ; Hierarchical model ; Fuzzy probabilities ; Imprecise probabilities ; Statistical inconsistency
Likelihood function ; Hierarchical model ; Fuzzy probabilities ; Imprecise probabilities ; Statistical inconsistency
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.172.6323
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/smps08.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.172.6323
http://www.stat.unimuenchen.de/%7Ecattaneo/publications/smps08.pdf
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(35) Ranjard, F
(35) Reucroft, S
(35) Romero, A
(35) Romero, L
(35) Ronchese, P
(35) Rovelli, T
(35) Ruiz, H
(35) Rykaczewski, H
(35) Salicio, J
(35) Sanguinetti, G
(35) Sciacca, C
(35) Selvaggi, G
Author:
Subject
(10) phys hexp physics high energy physics experiment
(8) higgs boson
(6) effective coupling constants
(6) electron positron physics
(6) electroweak interactions
(6) fermion antifermion production
(6) neutral weak current
(6) technische reports
(6) tests of the standard model
(6) top quark
(5) ddc 510
(5) decays of heavy intermediate gauge bosons
(5) experiment hep
(5) radiative corrections
(5) w boson
(5) z boson
(4) particle physics experiment
(4) physics
(4) supersymmetric standard model
(3) conflict
(3) detectors and experimental techniques
(3) imprecise probabilities
(3) particles fields
(3) settore fis 01 fisica sperimentale
(2) angle bhabha scattering
(2) associativity
(2) b c meson
(2) bayes theorem
(2) carlo event generator
(2) combination
(2) cross section asymmetry
(2) dempster s rule
(2) digital resources
(2) e e collisions
(2) electric dipole moment
(2) electroweak symmetry breaking
(2) elementary particle physics
(2) explicit cp violation
(2) fermion pair production
(2) flavor independent search
(2) forward backward asymmetry
(2) grey literature
(2) hadronic z decays
(2) higgs boson production
(2) idempotency
(2) imprecise data
(2) independence
(2) instrumentation
(2) large hadron collider
(2) large transverse momentum
(2) lep
(2) medicine and health sciences
(2) minimal supersymmetric standard model
(2) monotonicity
(2) naive credal classifier
(2) nonspecificity
(2) nuclear physics
(2) opal detector
(2) open archives
(2) phenomenology hep
(2) phys hphe physics high energy physics...
(2) physics and astronomy
(2) precision measurements at the z resonance
(2) precision measurements at w pair energies
(2) production cross section
(2) propositional logic
(2) qc physics
(2) root s
(2) root s 189 gev
(2) semileptonic branching ratios
(2) settore fis 04 fisica nucleare e subnucleare
(2) softly broken supersymmetry
(2) superconducting super collider
(2) supergauge transformations
(2) theses
(2) to leading order
(2) top quark mass
(2) w boson mass
(2) z 0 decays
(2) z line shape
(1) 2006
(1) 62a01
(1) 62c05
(1) 7000 gev cms8000 gev cms
(1) adult
(1) aged
(1) alleles
(1) asymptotics
(1) b s0 branching ratio measured
(1) b s0 leptonic decay
(1) b s0 muon muon
(1) b s0 rare decay
(1) b0 branching ratio measured
(1) b0 leptonic decay
(1) b0 muon muon
(1) b0 rare decay
(1) bayesian networks
(1) belief functions
(1) boson
(1) brca1 protein
Subject:
Dewey Decimal Classification (DDC)
(18) Physics [53*]
(8) Medicine & health [61*]
(4) Statistics [31*]
(2) Mathematics [51*]
(1) Computer science, knowledge & systems [00*]
(1) Astronomy [52*]
Dewey Decimal Classification (DDC):
Year of Publication
(37) 2006
(16) 2013
(13) 2010
(12) 2011
(8) 2007
(7) 2012
(5) 1993
(5) 2008
(5) 2014
(2) 1996
(2) 2009
(1) 1992
(1) 2003
(1) 2005
Year of Publication:
Content Provider
(21) CiteSeerX
(14) UMass Amherst
(8) Joint Inst. for Nuclear Research: JINR Document...
(7) HAL  Hyper Article en Ligne
(7) CERN (Switzerland)
(6) Munich LMU: Open Access
(6) Oxford Univ.: Research Archive (ORA)
(5) Aachen RWTH: Publications
(4) Athens National Technical Univ.: DSpace
(4) London Univ. College: UCL Discovery
(4) Lund Univ. Publications (LUP)
(3) Glasgow Univ.
(3) Milan Univ.: Archivio Istituzionale della Ricerca
(2) DUMAS (France)
(2) Lausanne Ecole Polytechnique Fed.: Infoscience
(2) CCSD: memSIC
(2) Purdue Univ.: ePubs
(2) São Paulo UNESP: Repository
(2) Rotterdam Erasmus Univ.: RePub
(1) ArXiv.org
(1) London Brunel Univ.: Research Archive (BURA)
(1) Project Euclid
(1) DESY Hamburg
(1) London King's College: Research Portal
(1) LSH (Iceland)
(1) Southern Denmark Univ.: Research Output
(1) Huddersfield Univ.
(1) Queensland Univ.: UQ eSpace
(1) Wollongong Univ.
(1) Warwick Univ.: Warwick Research Archive Portal
Content Provider:
Language
(66) English
(49) Unknown
Language:
Document Type
(48) Text
(41) Article, Journals
(19) Unknown
(6) Reports, Papers, Lectures
(1) Reviews
Document Type:
Access
(93) Unknown
(22) Open Access
Access:
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