Takada Hellinton (27 results)
Bayesian Inference and Maximum Entropy Methods in Science and Engineering: MaxEnt 37, Jarinu, Brazil, July 09-14, 2017 (Springer Proceedings in Mathematics & Statistics, 239, Band 239) [Hardcover] Polpo, Adriano; Stern, Julio; Louzada, Francisco; Izbicki, Rafael and Takada, Hellinton
Polpo, Adriano; Stern, Julio; Louzada, Francisco; Izbicki, Rafael; Takada, Hellinton
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Bayesian Inference and Maximum Entropy Methods in Science and Engineering : Maxent 37, Jarinu, Brazil, July 09-14, 2017
Polpo, Adriano (EDT); Stern, Julio (EDT); Louzada, Francisco (EDT); Izbicki, Rafael (EDT); Takada, Hellinton (EDT)
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Bayesian Inference and Maximum Entropy Methods in Science and Engineering : Maxent 37, Jarinu, Brazil, July 09-14, 2017
Polpo, Adriano (EDT); Stern, Julio (EDT); Louzada, Francisco (EDT); Izbicki, Rafael (EDT); Takada, Hellinton (EDT)
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Bayesian Inference and Maximum Entropy Methods in Science and Engineering : Maxent 37, Jarinu, Brazil, July 09-14, 2017
Polpo, Adriano (EDT); Stern, Julio (EDT); Louzada, Francisco (EDT); Izbicki, Rafael (EDT); Takada, Hellinton (EDT)
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Bayesian Inference and Maximum Entropy Methods in Science and Engineering : Maxent 37, Jarinu, Brazil, July 09-14, 2017
Polpo, Adriano (EDT); Stern, Julio (EDT); Louzada, Francisco (EDT); Izbicki, Rafael (EDT); Takada, Hellinton (EDT)
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Published by Springer 2019
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Taschenbuch. Condition: Neu. Bayesian Inference and Maximum Entropy Methods in Science and Engineering | MaxEnt 37, Jarinu, Brazil, July 09-14, 2017 | Adriano Polpo (u. a.) | Taschenbuch | Springer Proceedings in Mathematics & Statistics | xvi | Englisch | 2019 | Springer | EAN 9783030081867 | Verantwortliche Person für die EU:…Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Published by Springer International Publishing, Springer International Publishing 2019
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in São Carlos, Brazil, aim to expand the available research on Bayesian methods and promote thei…r application in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications.Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis.For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. Areas of application in these workshops include astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, materials science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling are also regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, as well as novel applications of inferenceto illuminate the foundations of physical theories, are also of keen interest.
Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in São Carlos, Brazil, aim to expand the available research on Bayesian methods and promote their appli…cation in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications.Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis.For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. Areas of application in these workshops include astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, materials science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling are also regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, as well as novel applications of inferenceto illuminate the foundations of physical theories, are also of keen interest.
Language: English
Published by Springer Verlag 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
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Language: English
Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Polpo, Adriano|Stern, Julio|Louzada, Francisco|Izbicki, Rafael|Takada, Hellinton
Language: English
Published by Springer International Publishing 2019
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Softcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Adriano Polpo, Ph.D., is an Associate Professor of Statistics at the Federal University of Sao Carlos (UFSCar, Brazil). He received his B.Sc. in Statistics from the State University of Campinas, his Ph.D. in Stati…stics from the University of .
Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Polpo, Adriano|Stern, Julio|Louzada, Francisco|Izbicki, Rafael|Takada, Hellinton
Language: English
Published by Springer International Publishing 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
- Print on Demand
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Adriano Polpo, Ph.D., is an Associate Professor of Statistics at the Federal University of Sao Carlos (UFSCar, Brazil). He received his B.Sc. in Statistics from the State University of Campinas, his Ph.D…. in Statistics from the University of .
Language: English
Published by Springer International Publishing Jan 2019 2019
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Softcover
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in São Carlos, Brazil, aim to expand the available research on Bayesian methods…and promote their application in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications.Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis.For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. Areas of application in these workshops include astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, materials science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling are also regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, as well as novel applications of inference to illuminate the foundations of physical theories, are also of keen interest. 320 pp. Englisch.
Language: English
Published by Springer International Publishing Jul 2018 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
- Hardcover
- Print on Demand
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in São Carlos, Brazil, aim to expand the available research on Bayesian methods and pro…mote their application in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications.Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis.For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. Areas of application in these workshops include astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, materials science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling are also regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, as well as novel applications of inference to illuminate the foundations of physical theories, are also of keen interest. 320 pp. Englisch.
Language: English
Published by Springer 2019
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Published by Springer 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Published by Springer, Springer International Publishing Jan 2019 2019
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Expands the available research on Bayesian methods and promotes their application in the scientific communitySpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.
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Published by Springer, Springer International Publishing Jul 2018 2018
Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Expands the available research on Bayesian methods and promotes their application in the scientific communitySpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.
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Series: Springer Proceedings in Mathematics & Statistics, Book 238 of 464. Book 238 of 464 - Springer Proceedings in Mathematics & Statistics
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