Search results for " Bayes."

showing 10 items of 173 documents

Towards Open Domain Chatbots—A GRU Architecture for Data Driven Conversations

2018

Understanding of textual content, such as topic and intent recognition, is a critical part of chatbots, allowing the chatbot to provide relevant responses. Although successful in several narrow domains, the potential diversity of content in broader and more open domains renders traditional pattern recognition techniques inaccurate. In this paper, we propose a novel deep learning architecture for content recognition that consists of multiple levels of gated recurrent units (GRUs). The architecture is designed to capture complex sentence structure at multiple levels of abstraction, seeking content recognition for very wide domains, through a distributed scalable representation of content. To …

010302 applied physicsStructure (mathematical logic)Service (systems architecture)Computer sciencebusiness.industryDeep learning02 engineering and technologycomputer.software_genre01 natural sciencesChatbotNaive Bayes classifier020204 information systems0103 physical sciencesPattern recognition (psychology)0202 electrical engineering electronic engineering information engineeringArtificial intelligenceArchitecturebusinesscomputerNatural language processingSentence
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A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distri…

2019

Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonsp…

0106 biological sciences0301 basic medicineHierarchical Bayesian modelsArabidopsis thalianaRange (biology)Bayesian probabilitySpecies distributionArabidopsisGenetic admixtureBiologyResidual010603 evolutionary biology01 natural sciences03 medical and health sciencesAfrica NorthernStatisticsGeneticsSpatial analysisEcology Evolution Behavior and SystematicsSpatial AnalysisPortugalPlant DispersalGenetic heterogeneityGlobal climate changePhylogeographyGenetics Population030104 developmental biologySpainGenetic structureGeographic genetic structureMaxentPeptidesSpatial autocorrelationBiotechnology
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Does the genetic diversity among pubescent white oaks in southern Italy, Sicily and Sardinia islands support the current taxonomic classification?

2020

AbstractMolecular diversity analysis of deciduous pubescent oaks was conducted for populations from Calabria, Sicily and Sardinia. The aims of this study were twofold. First, to provide data on the genetic diversity of pubescent oaks from an understudied area which currently exhibits one of the highest concentrations of pubescent oak species in Europe. Second, to verify if these groups of oaks are genetically distinct and if their identification is in accordance with the current taxonomic classification. Molecular analyses of leaf material of 480 trees from seventeen populations belonging to putatively different pubescent oak species (Quercus amplifolia,Q. congesta,Q. dalechampii,Q. ichnusa…

0106 biological sciencesBiogeographyBayesian analysisZoologyPlant ScienceBiology010603 evolutionary biology01 natural sciences03 medical and health sciencesBiogeography Bayesian analysis Genetic variation Nuclear microsatellites EST-SSRs Pubescent oaks TaxonomyGenetic variationGenetic variation030304 developmental biologyBayesian analysis; Biogeography; EST-SSRs; Genetic variation; Nuclear microsatellites; Pubescent oaks; TaxonomyTaxonomy0303 health sciencesGenetic diversityNuclear microsatellitesForestrylanguage.human_languageEST-SSRsPubescent oaksDeciduousGenetic distanceBiogeographySettore BIO/03 - Botanica Ambientale E ApplicatalanguageTaxonomy (biology)Species richnessSicilian
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Calibrating Expert Assessments Using Hierarchical Gaussian Process Models

2020

Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…

0106 biological sciencesComputer sciencepäätöksentekoRECONCILIATIONInferencecomputer.software_genre01 natural sciencesSTOCK ASSESSMENTenvironmental management010104 statistics & probabilityJUDGMENTSELICITATIONkalakantojen hoito111 Mathematicstilastolliset mallitReliability (statistics)Applied Mathematicsgaussiset prosessitfisheries sciencebias correctionexpert elicitationPROBABILITY62P1260G15symbols62F15Statistics and ProbabilityarviointimenetelmätBayesian probabilityenvironmental management.Bayesian inferenceMachine learningHEURISTICSsymbols.namesakeasiantuntijatMANAGEMENT0101 mathematicsGaussian processGaussian processCATCH LIMITSbusiness.industrybayesilainen menetelmä010604 marine biology & hydrobiologyUnivariateExpert elicitationOPINIONSupra BayesArtificial intelligenceHeuristicsbusinessFISHERIEScomputerBayesian Analysis
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Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates

2019

Abstract The assessment of diversity and similarity is relevant in monitoring the status of ecosystems. The respective indicators are based on the taxonomic composition of biological communities of interest, currently estimated through the proportions computed from sampling multivariate counts. In this work we present a novel method to estimate the taxonomic composition able to work even with a single sample and no covariates, when data are affected by overdispersion. The presence of overdispersion in taxonomic counts may be the result of significant environmental factors which are often unobservable but influence communities. Following the empirical Bayes approach, we combine a Bayesian mo…

0106 biological sciencesMultivariate statisticsBiological dataEmpirical Bayesian estimationEcologyTaxonomic compositionGeneral Decision SciencesEnvironmental monitoring010501 environmental sciencesBayesian inference010603 evolutionary biology01 natural sciencesBiodiversity assessment; Dirichlet-Multinomial model; Empirical Bayesian estimation; Environmental monitoring; Taxonomic compositionMarginal likelihoodBayes' theoremOverdispersionStatisticsTaxonomic rankDirichlet-Multinomial modelBiodiversity assessmentEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEmpirical Bayes methodMathematics
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Dealing with physical barriers in bottlenose dolphin (Tursiops truncatus) distribution

2019

Abstract Worldwide, cetacean species have started to be protected, but they are still very vulnerable to accidental damage from an expanding range of human activities at sea. To properly manage these potential threats we need a detailed understanding of the seasonal distributions of these highly mobile populations. To achieve this goal, a growing effort has been underway to develop species distribution models (SDMs) that correctly describe and predict preferred species areas. However, accuracy is not always easy to achieve when physical barriers, such as islands, are present. Indeed, SDMs assume, if only implicitly, that the spatial effect is stationary, and that correlation is only depende…

0106 biological sciencesRange (biology)Bayesian probabilitySpecies distributionDistribution (economics)Sede Central IEO010603 evolutionary biology01 natural sciencesINLAPesqueríasArchipelago de La MaddalenaSPDEgeographyCetaceansgeography.geographical_feature_categorybiologybusiness.industry010604 marine biology & hydrobiologyEcological ModelingEnvironmental resource managementBottlenose dolphinbiology.organism_classificationPhysical BarrierHabitatArchipelagoHierarchical Bayesian spatial modelsbusinessEcological Modelling
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Monitoring internet trade to inform species conservation actions

2017

Specimens, parts and products of threatened species are now commonly traded on the internet. This could threaten the survival of some wild populations if inadequately regulated. We outline two methods to monitor internet sales of threatened species in order to assess potential threats and inform conservation actions. Our first method combines systematic monitoring of online offers of plants for sale over the internet with consultation by experts experienced in identifying plants collected from the wild based on images of the specimens, species identity and details of the trade. Our second method utilises a computational model, trained using Bayesian techniques to records that have been clas…

0106 biological sciencesSettore BIO/07 - EcologiaEcologybusiness.industry010604 marine biology & hydrobiologyInternet privacyfood and beverages010603 evolutionary biology01 natural scienceslcsh:QK1-989Geographylcsh:Botanylcsh:ZoologySettore BIO/03 - Botanica Ambientale E ApplicataThe InternetAdenia Commiphora Operculicarya Uncarina Machine learning Infer.NET Naive Bayes classifierlcsh:QL1-991businessNature and Landscape Conservation
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Bayesian approach to urinary ESBL-producing Escherichia coli

2014

This is a retrospective study about the prevalence of ESBL-producing Escherichia coli (EEC) in urinary specimens from patients from the Comunitat Valenciana from January 2007 to December 2008. Data were retrieved from RedMIVA, and Bayesian generalized linear mixed models were considered to study the prevalence of EEC with regard to demographical and microbiological factors. The total number of infections considered was 164,502, the amount of urinary isolates was 70,827 belonging to 49,304 different patients, and 5,161 (7.3%) of the urinary isolates were EEC. Three out of four E. coli were isolated in women (76.8%), men showed higher rates of EEC (9.7% in men vs. 6.5% in women). EEC patients…

0301 basic medicinemedicine.medical_specialtyUrinary system030106 microbiologyPharmacologymedicine.disease_causePharmacovigilance03 medical and health sciencesAntibiotic resistanceInternal medicineControlMedicineRisk factorEscherichia colibusiness.industryMicrobiologia mèdicaRetrospective cohort studyAntimicrobialOmicsCiprofloxacinstomatognathic diseasesEstadística bayesianaBacteris patògensAntimicrobialbusinessmedicine.drug
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Defining classifier regions for WSD ensembles using word space features

2006

Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…

0303 health sciencesProbability learningWord-sense disambiguationComputer sciencebusiness.industryPattern recognition02 engineering and technologyDecision ruleSupport vector machine03 medical and health sciencesNaive Bayes classifier0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingStatistical analysisArtificial intelligencePolysemybusinessClassifier (UML)030304 developmental biology
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Particle identification in ALICE: a Bayesian approach

2016

We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss ($\mathrm{d}E/\mathrm{d}x$) and time-of-flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels ${\rm K}^0_S \righta…

:Kjerne- og elementærpartikkelfysikk: 431 [VDP]Monte Carlo methodGeneral Physics and AstronomyPID controllerPP01 natural sciencesParticle identificationHigh Energy Physics - ExperimentParticle identificationHigh Energy Physics - Experiment (hep-ex)ALICEHadron-Hadron scattering (experiments)Heavy-ion collisionNuclear and High Energy Physics Hadron-Hadron scattering (experiments) Heavy Ion Experiments Heavy-ion collision Quark gluon plasma Particle identification Bayesianscattering [p p][PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Nuclear Experiment (nucl-ex)Detectors and Experimental TechniquesNuclear ExperimentNuclear ExperimentPhysicsefficiency [particle identification]PB COLLISIONSVDP::Kjerne- og elementærpartikkelfysikk: 431Monte Carlo [numerical calculations]PB COLLISIONS PP PERFORMANCE.:Mathematics and natural scienses: 400::Physics: 430::Nuclear and elementary particle physics: 431 [VDP]PRIRODNE ZNANOSTI. Fizika.Time of flight:Nuclear and elementary particle physics: 431 [VDP]VDP::Nuclear and elementary particle physics: 431performancemomentum spectrum [charged particle]Nuclear and High Energy PhysicsParticle physicsMesoneducationBayesian probabilityFOS: Physical sciencesQuark gluon plasma[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]114 Physical sciencesBayesianNuclear physicsPhysics and Astronomy (all)PionHeavy Ion Experiments0103 physical sciencesddc:530010306 general physics010308 nuclear & particles physicsBayesian approach:Matematikk og naturvitenskap: 400::Fysikk: 430::Kjerne- og elementærpartikkelfysikk: 431 [VDP]ALICE experimentPERFORMANCEparticle identification ; Bayesian approachNATURAL SCIENCES. Physics.PB COLLISIONS; TEV; PP; PERFORMANCEPhysics - Data Analysis Statistics and ProbabilityQuark–gluon plasmaBayesian [statistics]TEVHigh Energy Physics::Experimentparticle identificationData Analysis Statistics and Probability (physics.data-an)
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