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Machine Learning A Probabilistic Perspective【電子書籍】 Kevin P. MurphyMachine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)The Probabilistic Revolution, Volume 2: Ideas in the Sciences (The MIT Press)Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) (English Edition)Probabilistic Theory of Mean Field Games with Applications I Mean Field FBSDEs, Control, and Games【電子書籍】 Fran ois DelarueThe Emergence of Probability: A Philosophical Study of Early Ideas About Probability Induction and Statistical Inference (Cambridge Series on Statistical And Probabilistic Mathematics)Extensions and Restrictions of Generalized Probabilistic Theories【電子書籍】 Jonathan SteinbergProbabilistic Machine Learning: Advanced Topics (Adaptive Computation and Machine Learning series) (English Edition)Probabilistic and Causal Inference: The Works of Judea Pearl (ACM Books)Probabilistic Robotics【電子書籍】 Sebastian Thrun（出版社）The MIT Press Probabilistic Robotics 1冊 978-0-262-20162-9Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series) (English Edition)オンデマンド版 技術分野におけるリスクアセスメント / 原タイトル:Probabilistic Risk Assessment of Engineering Systems 本/雑誌 (単行本 ムック) / MarkG.Stewart/原著 RobertE.Melchers/原著 酒井信介/監訳 小林英男/〔ほか〕共訳Random Graphs and Complex Networks (Cambridge in Statistical and Probabilistic Mathematics, 2)Probability and Computing Randomization and Probabilistic Techniques in Algorithms and Data Analysis【電子書籍】 Michael MitzenmacherReliability and Probabilistic Safety Assessment in Multi-Unit Nuclear Power Plants【電子書籍】 Senthil C. KumarBayesian Analysis with Python A practical guide to probabilistic modeling【電子書籍】 Osvaldo MartinBrittle Fracture and Damage of Brittle Materials and Composites Statistical-Probabilistic Approaches【電子書籍】 Jacques LamonProbabilistic Methods Applied to Electric Power Systems Proceedings of the First International Symposium, Toronto, Canada, 11 13 July 1986【電子書籍】Probabilistic Machine Learning for Finance and Investing A Primer to Generative AI with Python【電子書籍】 Deepak K. KanungoProbabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python (English Edition)Probabilistic Machine Learning: An Introduction PROBABILISTIC MACHINE LEARNING （Adaptive Computation and Machine Learning） Kevin P. Murphy洋書 Paperback, Proceedings of the Workshop on Probabilistic Flood Hazard Assessment (PFHA): U.S. NRC Headquarters Rockville, MarylandBayesian Analysis with Python Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ, 2nd Edition【電子書籍】 Osvaldo MartinNonuniformly Hyperbolic Attractors Geometric and Probabilistic Aspects【電子書籍】 Jos F. AlvesStudy on Probabilistic Model Building Genetic Network ProgrammingCombining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications【電子書籍】 Andrew PownukProbabilistic Machine Learning An Introduction【電子書籍】 Kevin P. MurphyAn Introduction to Probabilistic Number Theory (Cambridge Studies in Advanced Mathematics Book 192) (English Edition)18th International Probabilistic Workshop IPW 2020【電子書籍】

Machine Learning A Probabilistic Perspective【電子書籍】[ Kevin P. Murphy ]

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  • ＜p＞＜strong＞A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.＜/strong＞＜/p＞ ＜p＞Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.＜/p＞ ＜p＞The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated wit...

    • Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

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    The Probabilistic Revolution, Volume 2: Ideas in the Sciences (The MIT Press)

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    Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) (English Edition)

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    Probabilistic Theory of Mean Field Games with Applications I Mean Field FBSDEs, Control, and Games【電子書籍】[ Fran?ois Delarue ]

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  • ＜p＞This two-volume book offers a comprehensive treatment of the probabilistic approach to mean field game models and their applications. The book is self-contained in nature and includes original material and applications with explicit examples throughout, including numerical solutions.＜/p＞ ＜p＞Volume I of the book is entirely devoted to the theory of mean field games without a common noise. The first half of the volume provides a self-contained introduction to mean field games, starting from concrete illustrations of games with a finite number of players, and ending with ready-for-use solvability results. Readers are provided with the tools necessary for the solution of forward-backward stochastic differential equations of the McKean-Vlasov type at the core of the probabilistic approach. The second half of this volume focuses on the main principles of analysis on the Wasserstein space. It includes Lions' approach to the Wasserstein differential calculus, and the applications o...

    • The Emergence of Probability: A Philosophical Study of Early Ideas About Probability Induction and Statistical Inference (Cambridge Series on Statistical And Probabilistic Mathematics)

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    Extensions and Restrictions of Generalized Probabilistic Theories【電子書籍】[ Jonathan Steinberg ]

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  • ＜p＞Generalized probabilistic theories (GPTs) allow us to write quantum theory in a purely operational language and enable us to formulate other, vastly different theories. As it turns out, there is no canonical way to integrate the notion of subsystems within the framework of convex operational theories. Sections can be seen as generalization of subsystems and describe situations where not all possible observables can be implemented. Jonathan Steinberg discusses the mathematical foundations of GPTs using the language of Archimedean order unit spaces and investigates the algebraic nature of sections. This includes an analysis of the category theoretic structure and the transformation properties of the state space. Since the Hilbert space formulation of quantum mechanics uses tensor products to describe subsystems, he shows how one can interpret the tensor product as a special type of a section. In addition he applies this concept to quantum theory and compares it with the formulati...

    • Probabilistic Machine Learning: Advanced Topics (Adaptive Computation and Machine Learning series) (English Edition)

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    Probabilistic and Causal Inference: The Works of Judea Pearl (ACM Books)

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    Probabilistic Robotics【電子書籍】[ Sebastian Thrun ]

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  • ＜p＞＜strong＞An introduction to the techniques and algorithms of the newest field in robotics.＜/strong＞＜/p＞ ＜p＞Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers deali...

    • （出版社）The MIT Press Probabilistic Robotics 1冊 978-0-262-20162-9

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  • （出版社）The　MIT　Press Probabilistic Robotics 1冊●著者：Thrun, Sebastian/Burgard, Wolfram/Fox, Dieter●和文：確率的ロボティックス●頁数他：668 p.●装丁：Hard●出版社：The MIT Press●発行日：2005/9/20

    • Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series) (English Edition)

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    [オンデマンド版] 技術分野におけるリスクアセスメント / 原タイトル:Probabilistic Risk Assessment of Engineering Systems[本/雑誌] (単行本・ムック) / MarkG.Stewart/原著 RobertE.Melchers/原著 酒井信介/監訳 小林英男/〔ほか〕共訳

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  • ご注文前に必ずご確認ください＜商品説明＞※本商品はオンデマンド製品です。そのため、在庫表記が「メーカー在庫見込あり:1-3週間」もしくは「お取り寄せ:1-3週間」の場合、ご注文からお届けまでに約1ヶ月程度かかりますことを予めご了承ください＜収録内容＞第1章 緒言第2章 リスク源第3章 システムのモデル化第4章 システム要素の性能第5章 ヒューマンエラーとヒューマン信頼性のデータ第6章 システム評価第7章 リスク受け入れの基準付録A 適用事例＜アーティスト／キャスト＞佐々木哲也(演奏者)　小林英男(演奏者)＜商品詳細＞商品番号：NEOBK-994232メディア：本/雑誌重量：340g発売日：2011/08JAN：9784627945791[オンデマンド版] 技術分野におけるリスクアセスメント / 原タイトル:Probabilistic Risk Assessment of Engineering Systems[本/雑誌] (単行本・ムック) / MarkG.Stewart/原著 RobertE.Melchers/原著 酒井信介/監訳 小林英男/〔ほか〕共訳2011/08発売

    • Random Graphs and Complex Networks (Cambridge in Statistical and Probabilistic Mathematics, 2)

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    Probability and Computing Randomization and Probabilistic Techniques in Algorithms and Data Analysis【電子書籍】[ Michael Mitzenmacher ]

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  • ＜p＞Greatly expanded, this new edition requires only an elementary background in discrete mathematics and offers a comprehensive introduction to the role of randomization and probabilistic techniques in modern computer science. Newly added chapters and sections cover topics including normal distributions, sample complexity, VC dimension, Rademacher complexity, power laws and related distributions, cuckoo hashing, and the Lovasz Local Lemma. Material relevant to machine learning and big data analysis enables students to learn modern techniques and applications. Among the many new exercises and examples are programming-related exercises that provide students with excellent training in solving relevant problems. This book provides an indispensable teaching tool to accompany a one- or two-semester course for advanced undergraduate students in computer science and applied mathematics.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※...

    • Reliability and Probabilistic Safety Assessment in Multi-Unit Nuclear Power Plants【電子書籍】[ Senthil C. Kumar ]

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  • ＜p＞Reliability and Probabilistic Safety Assessment in Multi-Unit Nuclear Power Plants presents the risk contributions from single and multi-unit Nuclear Power Plants to help aggregate the risks that may arise due to applicable hazards and operating states. The book combines the key features of multi-unit risk assessment in one resource, reviewing the practices adopted in various countries around the globe to exemplify the dependencies between units on a site. These dependencies include multi-unit interactions, environmental stresses, the sharing of systems, and the sharing of human resource in a control room, factors which can all introduce an increase potential for heightened accident conditions. This book helps readers systematically identify events and evaluate techniques of possible accident outcomes within multi-units. It serves as a ready reference for PSA analysts in identifying a suitable site and the sharing of resources, while carrying out multi-unit risk assessments to ...

    • Bayesian Analysis with Python A practical guide to probabilistic modeling【電子書籍】[ Osvaldo Martin ]

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  • ＜p＞＜b＞Learn the fundamentals of Bayesian modeling using state-of-the-art Python libraries, such as PyMC, ArviZ, Bambi, and more, guided by an experienced Bayesian modeler who contributes to these libraries＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Conduct Bayesian data analysis with step-by-step guidance＜/li＞＜li＞Gain insight into a modern, practical, and computational approach to Bayesian statistical modeling＜/li＞＜li＞Enhance your learning with best practices through sample problems and practice exercises＜/li＞＜li＞Purchase of the print or Kindle book includes a free PDF eBook.＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞The third edition of Bayesian Analysis with Python serves as an introduction to the main concepts of applied Bayesian modeling using PyMC, a state-of-the-art probabilistic programming library, and other libraries that support and facilitate modeling like ArviZ, for exploratory analysis of Bayesian models; Bambi, for flexible and easy hierarchical li...

    • Brittle Fracture and Damage of Brittle Materials and Composites Statistical-Probabilistic Approaches【電子書籍】[ Jacques Lamon ]

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  • ＜p＞Flaws are the principal source of fracture in many materials, whether brittle or ductile, whether nearly homogeneous or composite. They are introduced during either fabrication or surface preparation or during exposure to aggressive environments (e. g. oxidation, shocks). The critical flaws act as stress concentrators and initiate cracks that propagate instantaneously to failure in the absence of crack arrest phenomena as encountered in brittle materials. This book explores those brittle materials susceptible to crack arrest and the flaws which initiate crack induced damage. A detailed description of microstructural features covering numerous brittle materials, including ceramics, glass, concrete, metals, polymers and ceramic fibers to help you develop your knowledge of material fracture. Brittle Failure and Damage of Brittle Materials and Composites outlines the technological progress in this field and the need for reliable systems with high performances to help you advance th...

    • Probabilistic Methods Applied to Electric Power Systems Proceedings of the First International Symposium, Toronto, Canada, 11?13 July 1986【電子書籍】

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  • ＜p＞Probabilistic Methods Applied to Electric Power Systems contains the proceedings of the First International Symposium held in Toronto, Ontario, Canada, on July 11-13, 1986. The papers explore significant technical advances that have been made in the application of probability methods to the design of electric power systems. This volume is comprised of 65 chapters divided into 10 sections and begins by discussing the probabilistic methodologies used in the assessment of power system reliability and structural design. The following chapters focus on the applications of probabilistic techniques to the analysis and design of transmission systems and structures; evaluation of design and reliability of distribution systems; system planning; and assessment of performance of transmission system components such as insulators, tower joints, and foundations. The probability-based procedures for dealing with data bases such as wind load and ice load are also considered, along with the effe...

    • Probabilistic Machine Learning for Finance and Investing A Primer to Generative AI with Python【電子書籍】[ Deepak K. Kanungo ]

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  • ＜p＞There are several reasons why probabilistic machine learning represents the next-generation ML framework and technology for finance and investing. This generative ensemble learns continually from small and noisy financial datasets while seamlessly enabling probabilistic inference, retrodiction, prediction, and counterfactual reasoning. Probabilistic ML also lets you systematically encode personal, empirical, and institutional knowledge into ML models.＜/p＞ ＜p＞Whether they're based on academic theories or ML strategies, all financial models are subject to modeling errors that can be mitigated but not eliminated. Probabilistic ML systems treat uncertainties and errors of financial and investing systems as features, not bugs. And they quantify uncertainty generated from inexact inputs and outputs as probability distributions, not point estimates. This makes for realistic financial inferences and predictions that are useful for decision-making and risk management.＜/p＞ ＜p＞Unl...

    • Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python (English Edition)

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    Probabilistic Machine Learning: An Introduction PROBABILISTIC MACHINE LEARNING （Adaptive Computation and Machine Learning） [ Kevin P. Murphy ]

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  • PROBABILISTIC MACHINE LEARNING Adaptive Computation and Machine Learning Kevin P. Murphy MIT PR2022 Hardcover English ISBN：9780262046824 洋書 Computers & Science（コンピューター＆科学） Computers

    • 洋書 Paperback, Proceedings of the Workshop on Probabilistic Flood Hazard Assessment (PFHA): U.S. NRC Headquarters Rockville, Maryland

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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • Bayesian Analysis with Python Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ, 2nd Edition【電子書籍】[ Osvaldo Martin ]

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  • ＜p＞＜strong＞Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ＜/li＞ ＜li＞A modern, practical and computational approach to Bayesian statistical modeling＜/li＞ ＜li＞A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models.＜/p＞ ＜p＞The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as gene...

    • Nonuniformly Hyperbolic Attractors Geometric and Probabilistic Aspects【電子書籍】[ Jos? F. Alves ]

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  • ＜p＞This monograph offers a coherent, self-contained account of the theory of Sinai?Ruelle?Bowen measures and decay of correlations for nonuniformly hyperbolic dynamical systems.＜/p＞ ＜p＞A central topic in the statistical theory of dynamical systems, the book in particular provides a detailed exposition of the theory developed by L.-S. Young for systems admitting induced maps with certain analytic and geometric properties. After a brief introduction and preliminary results, Chapters 3, 4, 6 and 7 provide essentially the same pattern of results in increasingly interesting and complicated settings. Each chapter builds on the previous one, apart from Chapter 5 which presents a general abstract framework to bridge the more classical expanding and hyperbolic systems explored in Chapters 3 and 4 with the nonuniformly expanding and partially hyperbolic systems described in Chapters 6 and 7. Throughout the book, the theory is illustrated with applications.＜/p＞ ＜p＞A clear and detaile...

    • Study on Probabilistic Model Building Genetic Network Programming

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  • Xianneng Li／著早稲田大学モノグラフ 92本詳しい納期他、ご注文時はご利用案内・返品のページをご確認ください出版社名早稲田大学出版部出版年月2013年10月サイズ124P 30cmISBNコード9784657135155工学 電気電子工学 電気工学一般商品説明Study on Probabilistic Model Building Genetic Network Programmingスタデイ- オン プロバビリステイツク モデル ビルデイング ジエネテイツク ネツトワ-ク プログラミング STUDY ON PROBABILISTIC MODEL BUILDING GENETIC NETWORK PROGRAMMING ワセダ ダイガク※ページ内の情報は告知なく変更になることがあります。あらかじめご了承ください登録日2014/11/17

    • Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications【電子書籍】[ Andrew Pownuk ]

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  • ＜p＞How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc.＜/p＞ ＜p＞In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty.＜/p＞ ＜p＞The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn...

    • Probabilistic Machine Learning An Introduction【電子書籍】[ Kevin P. Murphy ]

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  • ＜p＞＜strong＞A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.＜/strong＞＜/p＞ ＜p＞This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.＜/p＞ ＜p＞＜em＞Probabilistic Machine Learning＜/em＞ grew out of the author’s 2012 book, ＜em＞Machine Learning: A Probabilistic Perspective＜/em＞. More than just a simple update, this is a completely new book that reflects the dramatic developme...

    • An Introduction to Probabilistic Number Theory (Cambridge Studies in Advanced Mathematics Book 192) (English Edition)

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    18th International Probabilistic Workshop IPW 2020【電子書籍】

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  • ＜p＞This volume presents the proceedings of the 18th International Probabilistic Workshop (IPW), which was held in Guimar?es, Portugal in May 2021. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない...
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