Search results for "bayesian"

showing 10 items of 604 documents

Bayesian PDF reweighting meets the Hessian methods

2016

Volume: 273 New data coming from the LHC experiments have a potential to extend the current knowledge of parton distribution functions (PDFs). As a short cut to the cumbersome and time consuming task of performing a new PDF fit, re weighting methods have been proposed. In this talk, we introduce the so-called Hessian re-weighting, valid for PDF fits that carried out a Hessian error analysis, and compare it with the better-known Bayesian methods. We determine the existence of an agreement between the two approaches, and illustrate this using the inclusive jet production at the LHC. Peer reviewed

Hessian matrixPhysicsNuclear and High Energy PhysicsParticle physicsLarge Hadron Colliderta114parton distribution functionsJet (mathematics)010308 nuclear & particles physicsBayesian probabilityPartonJET DATAre-weighting methodsPROTON114 Physical sciences01 natural sciencesBayesian re-weightingsymbols.namesakeError analysisPARTON DISTRIBUTIONS0103 physical sciencessymbolsLHCHessian re-weighting010306 general physicsNuclear and Particle Physics Proceedings
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PDF reweighting in the Hessian matrix approach

2014

We introduce the Hessian reweighting of parton distribution functions (PDFs). Similarly to the better-known Bayesian methods, its purpose is to address the compatibility of new data and the quantitative modifications they induce within an existing set of PDFs. By construction, the method discussed here applies to the PDF fits that carried out a Hessian error analysis using a non-zero tolerance $\Delta\chi^2$. The principle is validated by considering a simple, transparent example. We are also able to establish an agreement with the Bayesian technique provided that the tolerance criterion is appropriately accounted for and that a purely exponential Bayesian likelihood is assumed. As a practi…

Hessian matrixPhysicsParticle physicsNuclear and High Energy PhysicsStatistical methodsta114Bayesian probabilityFOS: Physical sciencesPartonQCDExponential functionHigh Energy Physics - Experimentsymbols.namesakeHigh Energy Physics - PhenomenologyHigh Energy Physics - Experiment (hep-ex)Distribution functionHigh Energy Physics - Phenomenology (hep-ph)Error analysissymbolsParton modelApplied mathematicsJournal of High Energy Physics
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Cronología bayesiana aplicada a las intervenciones de Lluís Pericot en Cueva de la Cocina (1941 y 1945)

2017

Este capítulo tiene como objetivo la comprensión de la estratigrafía en Cueva de la Cocina, y más en concreto de las intervenciones realizadas por Pericot en el año 1941 y 1945. Para ello se hará uso del conjunto de dataciones radiocarbónicas disponibles para dichas intervenciones sobre las que se elaborarán diferentes modelos cronológicos a partir de la estadística bayesiana. Finalmente sobre los resultados de la modelización cronológica se discierne en torno a la ocupación mesolítica de la cueva a lo largo del Mesolítico reciente (entidad arqueológica conocida como Mesolítico geométrico), haciendo hincapié en las diferentes fases culturales (Geométrico A y B) y sus rangos cronológicos. Th…

Historia [55]Estadística bayesianaNeolíticoMesolítico55:HistoriaCueva de la CocinaCarbono 14
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Inferring intentions through state representations in cooperative human-robot environments

2014

Humans and robots working safely and seamlessly together in a cooperative environment is one of the future goals of the robotics community. When humans and robots can work together in the same space, a whole class of tasks becomes amenable to automation, ranging from collaborative assembly to parts and material handling to delivery. Proposed standards exist for collaborative human-robot safety, but they focus on limiting the approach distances and contact forces between the human and the robot. These standards focus on reactive processes based only on current sensor readings. They do not consider future states or task-relevant information. A key enabler for human-robot safety in cooperative…

Human-robot collaborationOntology[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Intention recognitionBayesian[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]KittingReconnaissance de l'intentionManufacturingState relationsRCC8[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]SimulationUSARSim
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Bayesian approach for uncertainty quantification in water quality modelling: The influence of prior distribution

2010

Summary Mathematical models are of common use in urban drainage, and they are increasingly being applied to support decisions about design and alternative management strategies. In this context, uncertainty analysis is of undoubted necessity in urban drainage modelling. However, despite the crucial role played by uncertainty quantification, several methodological aspects need to be clarified and deserve further investigation, especially in water quality modelling. One of them is related to the “a priori” hypotheses involved in the uncertainty analysis. Such hypotheses are usually condensed in “a priori” distributions assessing the most likely values for model parameters. This paper explores…

HydrologySettore ICAR/03 - Ingegneria Sanitaria-AmbientaleComputer scienceBayesian approachUrban stormwater quality modellingContext (language use)Water quality modellingPrior knowledgeData qualityBayesian approach; Prior knowledge; Uncertainty assessment; Urban stormwater quality modellingPrior probabilityEconometricsSensitivity analysisUncertainty assessmentUncertainty quantificationUncertainty analysisReliability (statistics)Water Science and Technology
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Geographical variation in pharmacological prescription

2009

Promoting rational drug administration in treatments is one of the most important issues in Public Health. Bayesian hierarchical models are a very useful tool for incorporating geographical information into the analysis of pharmacological prescription data. They allow the mapping of spatial components which express the trend of geographical variation. In addition, these models are able to deal with uncertainty in a sequential way through prior distributions on parameters and hyperparameters. Bayes' theorem combines all types of information and provides the posterior distribution which is computed through Markov Chain Monte Carlo (MCMC) simulation methods. Simulated data for pharmacological …

HyperparameterMarkov chainBayesian probabilityPosterior probabilityLinear modelMarkov chain Monte CarloGeneralized linear mixed modelComputer Science Applicationssymbols.namesakeBayes' theoremModelling and SimulationModeling and SimulationEconometricssymbolsMathematicsMathematical and Computer Modelling
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A Novel System for Multi-level Crohn’s Disease Classification and Grading Based on a Multiclass Support Vector Machine

2020

Crohn’s disease (CD) is a chronic inflammatory condition of the gastrointestinal tract that can highly alter patient’s quality of life. Diagnostic imaging, such as Enterography Magnetic Resonance Imaging (E-MRI), provides crucial information for CD activity assessment. Automatic learning methods play a fundamental role in the classification of CD and allow to avoid the long and expensive manual classification process by radiologists. This paper presents a novel classification method that uses a multiclass Support Vector Machine (SVM) based on a Radial Basis Function (RBF) kernel for the grading of CD inflammatory activity. To validate the system, we have used a dataset composed of 800 E-MRI…

Hyperparameterbusiness.industryComputer scienceMulticlass support vector machineBayesian optimizationSupervised learningFeature extractionFeature reductionCrohn’s disease multi-level classification and gradingK-fold cross-validationPattern recognitionSupport vector machineRadial basis function kernelMedical imagingFeature extractionArtificial intelligencebusinessClassifier (UML)Supervised learningBayesian optimization
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Temperamentos afectivos y edad de inicio en pacientes bipolares tipo II

2016

Actualmente es imperante contar con indicadores que posibiliten realizar una detección temprana y correcta del trastorno bipolar en general, y del tipo II, en particular. Los temperamentos afectivos constituyen estilos de reactividad emocional temporalmente estables a lo largo del ciclo vital, con una importante base biológica. Dada la escasez de investigaciones al respecto, se exploraron posibles asociaciones entre la edad de inicio de 32 pacientes eutímicos con diagnóstico de trastorno bipolar tipo II y los temperamentos afectivos ciclotímico, depresivo, irritable, ansioso e hipertímico. Los participantes presentaron una edad media de 51,5 años (rango intercuartil 8) y el 65,6% de la mues…

Hyperthymic temperamentmedicine.medical_specialtymedia_common.quotation_subjectGeneral Engineeringdepresiónmedicine.diseasetemperamentoBipolar II disorderInterquartile rangeTEMPS-ABayesian multivariate linear regressioneutimiamedicineTemperamentBipolar disordertrastorno bipolarPsychiatryPsychologyInverse correlationDepression (differential diagnoses)media_common
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Using Bayesian networks to describe hydrologic processes

2014

Masteroppgave i Informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2014 The goal for this Masters thesis is to explore the use of dynamic Bayesian networks for describinghydrologic processes. The main intent is to try and provide better descriptions of the uncertainties thatare tied to dealing with such complex and partially unknown processes, while also trying to reducethese uncertainties. For this purpose I have translated part of a well known and widely useddeterministic model, the snow module of the HBV model, into a dynamic Bayesian network.

IKT590Bayesian networks ; hydrologic processes ; hydrologyVDP::Technology: 500::Information and communication technology: 550
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An interpolation-based data fusion scheme for enhancing the resolution of thermal image sequences

2014

In several human activities, such as agriculture and forest management, the monitoring of radiometric surface temperature is key. In particular both high spatial resolution and high acquisition rate are desirable but, due to the hardware limitations, these two characteristics are not met by the same sensor. The fusion of remotely sensed data acquired by sensors with different spatial and temporal resolution is a profitable choice to face this issue. When the real-time requirement is relaxed, the data sequence can be processed as a whole, allowing to improve the final result. Within this framework, we propose a novel batch sharpening strategy, relying on interpolation, data fusion and Bayesi…

Image fusionIrrigation ManagementSettore ING-INF/03 - TelecomunicazioniComputer sciencebusiness.industrySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaComputer Science Applications1707 Computer Vision and Pattern RecognitionSharpeningSensor fusionBayesian SmoothingThermal SharpeningMultitemporal AnalysiTemporal resolutionFace (geometry)Key (cryptography)Settore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliComputer visionArtificial intelligencebusinessMultisensor Data FusionEarth and Planetary Sciences (all)Settore ICAR/06 - Topografia E CartografiaSub-pixel resolutionInterpolation2014 IEEE Geoscience and Remote Sensing Symposium
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