نتائج البحث - "Markov chain Monte Carlo sampling"

Relation: https://eprints.qut.edu.au/242169/1/Bennett_et_al_2023_MODSIM.pdf; https://mssanz.org.au/modsim2023/files/bennett42.pdf; Bennett, Frederick, Botha, Imke, Adams, Matthew, & Drovandi, Chris (2023) Assimilating modelled dissolved inorganic nitrogen loads to monitored data using component-wise iterative ensemble Kalman inversion. In Vaze, Jai, Chilcott, Chris, Hutley, Lindsay, & Cuddy, Susan M. (Eds.) Proceedings of the 25th International Congress on Modelling and Simulation (MODSIM 2023). Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ), Australia, pp. 72-78.; https://eprints.qut.edu.au/242169/; Centre for Data Science; Faculty of Science; School of Mathematical Sciences

الاتاحة: https://eprints.qut.edu.au/242169/

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5

Academic Journal

Uncertainty quantification methodology for model parameters in sub-channel codes using MCMC sampling

المؤلفون: HE Xin, SONG Meiqi, LIU Xiaojing

المصدر: He jishu, Vol 46, Iss 12, Pp 120602-120602 (2023)

مصطلحات موضوعية: markov chain monte carlo sampling, surrogate model, uncertainty quantification, void fraction, inverse problem solving, Nuclear engineering. Atomic power, TK9001-9401

وصف الملف: electronic resource

Relation: http://www.hjs.sinap.ac.cn/thesisDetails#10.11889/j.0253-3219.2023.hjs.46.120602&lang=zh; https://doaj.org/toc/0253-3219

URL الوصول: https://doaj.org/article/f9f75d4e106541eda9a6bcabcdf8e125

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6

Academic Journal

Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers

المؤلفون: Fort, Gersende, Pascal, Barbara, Abry, Patrice, Pustelnik, Nelly

المساهمون: Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure de Lyon (ENS de Lyon), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Projet OpSiMorE, Fondation Simone et Cino Del Duca

المصدر: ISSN: 1053-587X ; IEEE Transactions on Signal Processing ; https://hal.science/hal-03611079 ; IEEE Transactions on Signal Processing, In press, 71, pp.888-900. ⟨10.1109/TSP.2023.3247142⟩.

مصطلحات موضوعية: Markov Chain Monte Carlo sampling, nonsmooth convex optimization, Bayesian inverse problems, credibility intervals, Covid19, reproduction number, [STAT.ME]Statistics [stat]/Methodology [stat.ME], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2203.09142; ARXIV: 2203.09142

الاتاحة: https://hal.science/hal-03611079
https://hal.science/hal-03611079v3/document
https://hal.science/hal-03611079v3/file/21CovidCI.pdf
https://doi.org/10.1109/TSP.2023.3247142

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7

Academic Journal

pySODM : simulating and optimizing dynamical models in Python 3

المؤلفون: Alleman, Tijs, Stevens, Christian, Baetens, Jan

المصدر: JOURNAL OF COMPUTATIONAL SCIENCE ; ISSN: 1877-7503 ; ISSN: 1877-7511

مصطلحات موضوعية: Mathematics and Statistics, Modeling framework, Differential equations, Gillespie simulation, Markov Chain Monte Carlo sampling, Enzyme kinetics, Mathematical epidemiology

وصف الملف: application/pdf

Relation: https://biblio.ugent.be/publication/01HCMD7A84A202Z7WP623ABPP1; http://doi.org/10.1016/j.jocs.2023.102148; https://biblio.ugent.be/publication/01HCMD7A84A202Z7WP623ABPP1/file/01HCMD7HWG846BXZ072RRJXQTE

الاتاحة: https://biblio.ugent.be/publication/01HCMD7A84A202Z7WP623ABPP1
http://hdl.handle.net/1854/LU-01HCMD7A84A202Z7WP623ABPP1
https://doi.org/10.1016/j.jocs.2023.102148
https://biblio.ugent.be/publication/01HCMD7A84A202Z7WP623ABPP1/file/01HCMD7HWG846BXZ072RRJXQTE

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8

Academic Journal

Generating impact maps from bomb craters automatically detected in aerial wartime images using marked point processes

المؤلفون: Christian Kruse, Dennis Wittich, Franz Rottensteiner, Christian Heipke

المصدر: ISPRS Open Journal of Photogrammetry and Remote Sensing, Vol 5, Iss , Pp 100017- (2022)

مصطلحات موضوعية: Marked point processes, Reversible Jump Markov Chain Monte Carlo sampling, Aerial wartime images, Bomb craters, Duds, Impact maps, Geography (General), G1-922, Surveying, TA501-625

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2667393222000060; https://doaj.org/toc/2667-3932

URL الوصول: https://doaj.org/article/6cfb029b4f534115aa624743db9b2924

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9

A Compositional Bayesian Semantics for Natural Language

المؤلفون: Bernardy, Jean-Philippe, 1978, Blanck, Rasmus, 1982, Chatzikyriakidis, Stergios, 1980, Lappin, Shalom, 1950

المصدر: Proceedings of the First International Workshop on Language Cognition and Computational Models, COLING 2018, August 20, 2018 Santa Fe, New Mexico, USA / Manjira Sinha, Tirthankar Dasgupta (Editors). :1-10

مصطلحات موضوعية: Natural Language Processing, Språkbehandling och datorlingvistik, Bayesian models, probabilistic semantics, probabilistic programming languages, Markov Chain Monte Carlo sampling

وصف الملف: electronic

URL الوصول: https://gup.ub.gu.se/publication/269415

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10

Academic Journal

Bayesian Hierarchical Models can Infer Interpretable Predictions of Leaf Area Index From Heterogeneous Datasets

المؤلفون: Olivera Stojanović, Bastian Siegmann, Thomas Jarmer, Gordon Pipa, Johannes Leugering

المصدر: Frontiers in Environmental Science, Vol 9 (2022)

مصطلحات موضوعية: bayesian hierarchical model, leaf area index, interpretability, markov chain monte carlo sampling, remote sensing, reflectance spectra, Environmental sciences, GE1-350

وصف الملف: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fenvs.2021.780814/full; https://doaj.org/toc/2296-665X

URL الوصول: https://doaj.org/article/69a6dee308b941fea4b43dd1989439b3

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11

Academic Journal

Bayesian Hierarchical Models can Infer Interpretable Predictions of Leaf Area Index From Heterogeneous Datasets

المؤلفون: Stojanović, Olivera, Siegmann, Bastian, Jarmer, Thomas, Pipa, Gordon, Leugering, Johannes

مصطلحات موضوعية: bayesian hierarchical model, leaf area index, interpretability, markov chain monte carlo sampling, remote sensing, reflectance spectra, ddc:580, ddc:004

وصف الملف: application/pdf

Relation: https://www.frontiersin.org/articles/10.3389/fenvs.2021.780814/full; https://doi.org/10.48693/206; Stojanović O, Siegmann B, Jarmer T, Pipa G and Leugering J (2022): Bayesian Hierarchical Models can Infer Interpretable Predictions of Leaf Area Index From Heterogeneous Datasets. Front. Environ. Sci. 9:780814.; https://osnadocs.ub.uni-osnabrueck.de/bitstream/ds-202211157782/1/fenvs_09_780814_2022_Stojanovi%c4%87.pdf

الاتاحة: https://doi.org/10.48693/206
https://doi.org/10.3389/fenvs.2021.780814
https://osnadocs.ub.uni-osnabrueck.de/bitstream/ds-202211157782/1/fenvs_09_780814_2022_Stojanovi%c4%87.pdf

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12

Investigation of maximum cooling loss uncertainty in piping network using Bayesian Markov Chain Monte Carlo method

المؤلفون: Huang, Pei, Huang, Gongsheng

المصدر: Energy Procedia. 143:258-263

مصطلحات موضوعية: HVAC, Capacity loss, Uncertainty, Bayesian inference, Markov Chain Monte Carlo Sampling

وصف الملف: print

URL الوصول: https://urn.kb.se/resolve?urn=urn:nbn:se:du-30856
https://doi.org/10.1016/j.egypro.2017.12.681
http://www.sciencedirect.com/science/article/pii/S1876610217364457

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13

Academic Journal

Semiparametric Bayesian classification with longitudinal markers

المؤلفون: De la Cruz Mesia, Rolando, Quintana, Fernando A., Mueller, Peter

مصطلحات موضوعية: dependent non-parametric model, discriminant analysis, longitudinal data, Markov chain Monte Carlo sampling, non-parametric modelling, random-effects models, species sampling models, DIRICHLET PROCESS MIXTURE, LINEAR MIXED MODELS, DISCRIMINANT-ANALYSIS, SAMPLING METHODS, PRIORS, DISTRIBUTIONS, INFERENCE, DENSITY, 03 Good Health and Well-being, 03 Salud y bienestar

وصف الملف: 19 páginas

Relation: MEDLINE:24368871; https://repositorio.uc.cl/handle/11534/76396; WOS:000245159600001

الاتاحة: https://repositorio.uc.cl/handle/11534/76396

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14

Report

Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers

المؤلفون: Fort, Gersende, Pascal, Barbara, Abry, Patrice, Pustelnik, Nelly

المساهمون: Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Projet OpSiMorE, Fondation Simone et Cino Del Duca

المصدر: https://hal.archives-ouvertes.fr/hal-03611079 ; 2022.

مصطلحات موضوعية: Markov chain Monte Carlo sampling, nonsmooth convex optimization, Bayesian inverse problems, credibility interval, Covid19, reproduction number, [STAT.ME]Statistics [stat]/Methodology [stat.ME], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [STAT.AP]Statistics [stat]/Applications [stat.AP], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]