Search results for "Importance"

showing 10 items of 81 documents

Compressed Particle Methods for Expensive Models With Application in Astronomy and Remote Sensing

2021

In many inference problems, the evaluation of complex and costly models is often required. In this context, Bayesian methods have become very popular in several fields over the last years, in order to obtain parameter inversion, model selection or uncertainty quantification. Bayesian inference requires the approximation of complicated integrals involving (often costly) posterior distributions. Generally, this approximation is obtained by means of Monte Carlo (MC) methods. In order to reduce the computational cost of the corresponding technique, surrogate models (also called emulators) are often employed. Another alternative approach is the so-called Approximate Bayesian Computation (ABC) sc…

FOS: Computer and information sciencesComputer scienceAstronomyModel selectionBayesian inferenceMonte Carlo methodBayesian probabilityAerospace EngineeringAstronomyInferenceMachine Learning (stat.ML)Context (language use)Bayesian inferenceStatistics - ComputationComputational Engineering Finance and Science (cs.CE)remote sensingimportance samplingStatistics - Machine Learningnumerical inversionparticle filteringElectrical and Electronic EngineeringUncertainty quantificationApproximate Bayesian computationComputer Science - Computational Engineering Finance and ScienceComputation (stat.CO)IEEE Transactions on Aerospace and Electronic Systems
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Heretical Mutiple Importance Sampling

2016

Multiple Importance Sampling (MIS) methods approximate moments of complicated distributions by drawing samples from a set of proposal distributions. Several ways to compute the importance weights assigned to each sample have been recently proposed, with the so-called deterministic mixture (DM) weights providing the best performance in terms of variance, at the expense of an increase in the computational cost. A recent work has shown that it is possible to achieve a trade-off between variance reduction and computational effort by performing an a priori random clustering of the proposals (partial DM algorithm). In this paper, we propose a novel "heretical" MIS framework, where the clustering …

FOS: Computer and information sciencesMean squared errorComputer scienceApplied MathematicsEstimator020206 networking & telecommunications02 engineering and technologyVariance (accounting)Statistics - Computation01 natural sciencesReduction (complexity)010104 statistics & probability[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingSignal Processing0202 electrical engineering electronic engineering information engineeringA priori and a posterioriVariance reduction0101 mathematicsElectrical and Electronic EngineeringCluster analysisAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImportance samplingComputation (stat.CO)ComputingMilieux_MISCELLANEOUS
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Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions

2021

We develop a Bayesian inference method for diffusions observed discretely and with noise, which is free of discretisation bias. Unlike existing unbiased inference methods, our method does not rely on exact simulation techniques. Instead, our method uses standard time-discretised approximations of diffusions, such as the Euler--Maruyama scheme. Our approach is based on particle marginal Metropolis--Hastings, a particle filter, randomised multilevel Monte Carlo, and importance sampling type correction of approximate Markov chain Monte Carlo. The resulting estimator leads to inference without a bias from the time-discretisation as the number of Markov chain iterations increases. We give conver…

FOS: Computer and information sciencesStatistics and ProbabilityDiscretizationComputer scienceMarkovin ketjutInference010103 numerical & computational mathematicssequential Monte CarloBayesian inferenceStatistics - Computation01 natural sciencesMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakediffuusio (fysikaaliset ilmiöt)FOS: MathematicsDiscrete Mathematics and Combinatorics0101 mathematicsHidden Markov modelComputation (stat.CO)Statistics - Methodologymatematiikkabayesilainen menetelmäApplied MathematicsProbability (math.PR)diffusionmatemaattiset menetelmätMarkov chain Monte CarloMarkov chain Monte CarloMonte Carlo -menetelmätNoiseimportance sampling65C05 (primary) 60H35 65C35 65C40 (secondary)Modeling and Simulationsymbolsmatemaattiset mallitStatistics Probability and Uncertaintymultilevel Monte CarloParticle filterAlgorithmMathematics - ProbabilityImportance samplingSIAM/ASA Journal on Uncertainty Quantification
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Investigating the Effects of Cell Size in Statistical Landslide Susceptibility Modelling for Different Landslide Typologies: A Test in Central–Northe…

2023

Optimally sizing grid cells is a relevant research issue in landslide susceptibility evaluation. In fact, the size of the adopted mapping units influences several aspects spanning from statistical (the number of positive/negative cases and prevalence and resolution/precision trade-off) and purely geomorphological (the representativeness of the mapping units and the diagnostic areas) to cartographic (the suitability of the obtained prediction images for the final users) topics. In this paper, the results of landslide susceptibility modelling in a 343 km2 catchment for three different types of landslides (rotational/translational slides, slope flows and local flows) using different pixel-size…

Fluid Flow and Transfer ProcessesSettore GEO/04 - Geografia Fisica E GeomorfologiaProcess Chemistry and TechnologyGeneral EngineeringMARSSicily (Italy)Computer Science Applicationsgrid cell size; variable importance; landslide susceptibility; MARS; Sicily (Italy)grid cell sizevariable importanceGeneral Materials Sciencelandslide susceptibilitySettore GEO/05 - Geologia ApplicataInstrumentationApplied Sciences
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A Metalloligand Approach for the Self-Assembly of a Magnetic Two-Dimensional Grid-of-Grids

2019

The efficient organization of discrete functional molecules into extended frameworks, while retaining their physical properties, is a mandatory requisite to move toward applications. Here we descri...

Functional importance010405 organic chemistryComputer scienceDistributed computingGeneral Materials ScienceGeneral Chemistry010402 general chemistryCondensed Matter PhysicsGrid01 natural sciences0104 chemical sciencesCrystal Growth & Design
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Les squelettes : structures d'interaction directe et intuitive avec des formes 3D

2014

The interactions in shape creation graphic applications are far from natural. The user tends to avoid as much as possible such applications and prefer to sketch or model his/her shape.To bridge this widening gap between computer and the general public, we focus on skeletons. They are intuitive shape representation models that we propose to use as direct and intuitive interaction structures.All skeletons suffer from very low quality as shape representation models, concerning the geometry of the shape they capture, the quantity of skeletal noise they contain or the lack of useful organization of their elements. Moreover, some functionalities that must be granted to skeletons are only partiall…

GarbingSquelette[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingHiérarchieHabillageRegularisationBoundariesBordsHierarchyNoise[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImportanceSkeleton[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Assessment of the interpretability of data mining for the spatial modelling of water erosion using game theory

2021

Abstract This study undertook a comprehensive application of 15 data mining (DM) models, most of which have, thus far, not been commonly used in environmental sciences, to predict land susceptibility to water erosion hazard in the Kahorestan catchment, southern Iran. The DM models were BGLM, BGAM, Cforest, CITree, GAMS, LRSS, NCPQR, PLS, PLSGLM, QR, RLM, SGB, SVM, BCART and BTR. We identified 18 factors usually considered as key controls for water erosion, comprising 10 factors extracted from a digital elevation model (DEM), three indices extracted from Landsat 8 images, a sediment connectivity index (SCI) and three other intrinsic factors. Three indicators consisting of MAE, MBE, RMSE, and…

Hazard (logic)Hazard map010504 meteorology & atmospheric sciencesMean squared error04 agricultural and veterinary sciencesCatchment managementcomputer.software_genre01 natural sciencesShapley additive explanationsSupport vector machineErosionTopological index040103 agronomy & agricultureFeature (machine learning)Permutation feature importance measure0401 agriculture forestry and fisheriesSpatial mappingData miningDigital elevation modelGame theorycomputer0105 earth and related environmental sciencesEarth-Surface ProcessesMathematicsInterpretability
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The Vascularization of Experimental and Human Primary Tumors: Comparative Morphometric and Morphologic Studies

1998

The importance of the blood vessel system in solid tumors has given rise to an increasing interest in this system as a direct target for tumor therapy, i.e. vascular targeting (Denekamp, 1984). Furthermore, its importance as a route for delivery of anticancer drugs (chemo- and immunotherapies) or photosensitizers (photodynamic laser therapy), as well as its modulatory influences on radiotherapy and hyperthermia — the former greatly depending on the amount of oxygen available, the latter on heat transfer — are evident. Numerous studies on the energy metabolism of solid tumors (Vaupel et al., 1987, 1989) have pointed out the functional importance of the blood vessel system and stress the need…

HyperthermiaChemistrymedicine.medical_treatmentEnergy metabolismTumor therapymedicine.diseaseRadiation therapymedicine.anatomical_structureLaser therapyFunctional importancemedicineCancer researchAmelanotic melanomaBlood vessel
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Guide to Practical Work with the Monte Carlo Method

2002

The guide is structured such that we proceed from the “easy” simulation methods and algorithms to the more sophisticated. For each method the algorithms are presented by the technique of stepwise refinement. We first present the idea and the basic outline. From then on we proceed by breaking up the larger logical and algorithmic structures into smaller ones, until we have reached the level of single basic statements. Sometimes we may elect not to go to such a depth and the reader is asked to fill in the gaps.

Logical conjunctionComputer scienceMonte Carlo methodDynamic Monte Carlo methodIsing modelMonte Carlo method in statistical physicsRandom walkAlgorithmImportance samplingMonte Carlo molecular modeling
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Identifying Drivers of Destination Attractiveness in a Competitive Environment: A Comparison of Approaches

2016

Abstract This study applies a demand-side analysis framework to assess drivers of destination attractiveness in consideration of competitor destinations. The framework, consisting of a relevance–determinance analysis (RDA) and a competitive-performance analysis (CPA), is further benchmarked against competing variants of importance–performance analysis (IPA). As this study reveals, the RDA+CPA framework significantly outperforms the IPA approaches with regard to the level of detail and validity of recommended managerial action. In particular, this study reveals that the original IPA framework of recommendations is not compatible for use with attributes that are characterized by large discrep…

MarketingAttractivenessConsumption (economics)Knowledge managementbusiness.industryStrategy and Management05 social sciencesLevel of detail (writing)Attractiveness ; Competitiveness ; Importance-performance analysis ; Relevance ; DeterminanceCompetitive advantageAction (philosophy)Tourism Leisure and Hospitality Management0502 economics and businessEconomics050211 marketingRelevance (information retrieval)Business and International ManagementMarketingDimension (data warehouse)business050212 sport leisure & tourismTourism
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