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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 9819827922 ISBN 13: 9789819827923
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 9819827922 ISBN 13: 9789819827923
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Some direct and inverse problems of mathematical physics
Language: English
Published by LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659523178 ISBN 13: 9783659523175
Condition: New.
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Mathematical Aspects of Inverse & Direct Problems of Thermoelasticity: Thermoelastic Problems
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659804800 ISBN 13: 9783659804809
Condition: New.
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, SG, 2026
ISBN 10: 9819827922 ISBN 13: 9789819827923
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physics, offering modern data-driven tools where traditional analytical and numerical methods fall short. As physical systems grow more complex or chaotic, deep learning provides efficient surrogates and physics-informed models capable of capturing dynamics and uncovering governing laws directly from data.This book introduces Neural ODEs, Physics-Informed Neural Networks (PINNs), and Hamiltonian and Lagrangian Neural Networks, showing how they enhance classical mechanics and PDE solvers for both forward and inverse problems. With Keras code examples, Google Colab notebooks, and practical exercises, this book serves researchers and students in physics, mathematics, and engineering seeking a concise, hands-on guide to applying deep learning in physical systems.
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Mathematical Aspects of Inverse & Direct Problems of Thermoelasticity: Thermoelastic Problems
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659804800 ISBN 13: 9783659804809
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Some direct and inverse problems of mathematical physics: Stationary and non-stationary diffusion
Language: English
Published by LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659523178 ISBN 13: 9783659523175
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Some direct and inverse problems of mathematical physics | Stationary and non-stationary diffusion
Language: English
Published by LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659523178 ISBN 13: 9783659523175
Taschenbuch. Condition: Neu. Some direct and inverse problems of mathematical physics | Stationary and non-stationary diffusion | Issabek Orazov | Taschenbuch | 128 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783659523175 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Direct and Inverse Problems of Mathematical Physics (International Society for Analysis, Applications and Computation)
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Direct and Inverse Problems of Mathematical Physics (INTERNATIONAL SOCIETY FOR ANALYSIS, APPLICATIONS AND)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Mathematical Aspects of Inverse & Direct Problems of Thermoelasticity | Thermoelastic Problems
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659804800 ISBN 13: 9783659804809
Taschenbuch. Condition: Neu. Mathematical Aspects of Inverse & Direct Problems of Thermoelasticity | Thermoelastic Problems | Suchitra Meshram | Taschenbuch | 164 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659804809 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Direct and Inverse Problems of Mathematical Physics
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Add to basketPaperback. Condition: Brand New. 552 pages. 6.00x1.25x9.00 inches. In Stock.
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Direct and Inverse Problems of Mathematical Physics
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. pp. 464.
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Taschenbuch. Condition: Neu. Direct and Inverse Problems of Mathematical Physics | R. P. Gilbert (u. a.) | Taschenbuch | International Society for Analysis, Applications and Computation | vii | Englisch | 2010 | Springer | EAN 9781441948182 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, SG, 2026
ISBN 10: 9819827922 ISBN 13: 9789819827923
US$ 119.99
US$ 87.04 shipping
Ships from United Kingdom to U.S.A.Quantity: 14 available
Add to basketPaperback. Condition: New. This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physics, offering modern data-driven tools where traditional analytical and numerical methods fall short. As physical systems grow more complex or chaotic, deep learning provides efficient surrogates and physics-informed models capable of capturing dynamics and uncovering governing laws directly from data.This book introduces Neural ODEs, Physics-Informed Neural Networks (PINNs), and Hamiltonian and Lagrangian Neural Networks, showing how they enhance classical mechanics and PDE solvers for both forward and inverse problems. With Keras code examples, Google Colab notebooks, and practical exercises, this book serves researchers and students in physics, mathematics, and engineering seeking a concise, hands-on guide to applying deep learning in physical systems.
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 981982723X ISBN 13: 9789819827237
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketHRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 981982723X ISBN 13: 9789819827237
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume consists of papers presented in the special sessions on 'Wave Phenomena and Related Topics', and 'Asymptotics and Homogenization' of the ISAAC'97 Congress held at the University of Delaware, during June 2-7, 1997. The ISAAC Congress coincided with a U.S.-Japan Seminar also held at the University of Delaware. The latter was supported by the National Science Foundation through Grant INT -9603029 and the Japan Society for the Promotion of Science through Grant MTCS-134. It was natural that the 'participants of both meetings should interact and consequently several persons attending the Congress also presented papers in the Seminar. The success of the ISAAC Congress and the U.S.-Japan Seminar has led to the ISAAC'99 Congress being held in Fukuoka, Japan during August 1999. Many of the same participants will return to this Seminar. Indeed, it appears that the spirit of the U.S.-Japan Seminar will be continued every second year as part of the ISAAC Congresses. We decided to include with the papers presented in the ISAAC Congress and the U.S.-Japan Seminar several very good papers by colleagues from the former Soviet Union. These participants in the ISAAC Congress attended at their own expense. This volume has the title Direct and Inverse Problems of Mathematical Physics which consists of the papers on scattering theory, coefficient identification, uniqueness and existence theorems, boundary controllability, wave propagation in stratified media, viscous flows, nonlinear acoustics, Sobolev spaces, singularity theory, pseudo differential operators, and semigroup theory.
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Direct and Inverse Problems of Mathematical Physics
Language: English
Published by Springer US, Springer US, 2000
ISBN 10: 0792360052 ISBN 13: 9780792360056
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume consists of papers presented in the special sessions on 'Wave Phenomena and Related Topics', and 'Asymptotics and Homogenization' of the ISAAC'97 Congress held at the University of Delaware, during June 2-7, 1997. The ISAAC Congress coincided with a U.S.-Japan Seminar also held at the University of Delaware. The latter was supported by the National Science Foundation through Grant INT -9603029 and the Japan Society for the Promotion of Science through Grant MTCS-134. It was natural that the 'participants of both meetings should interact and consequently several persons attending the Congress also presented papers in the Seminar. The success of the ISAAC Congress and the U.S.-Japan Seminar has led to the ISAAC'99 Congress being held in Fukuoka, Japan during August 1999. Many of the same participants will return to this Seminar. Indeed, it appears that the spirit of the U.S.-Japan Seminar will be continued every second year as part of the ISAAC Congresses. We decided to include with the papers presented in the ISAAC Congress and the U.S.-Japan Seminar several very good papers by colleagues from the former Soviet Union. These participants in the ISAAC Congress attended at their own expense. This volume has the title Direct and Inverse Problems of Mathematical Physics which consists of the papers on scattering theory, coefficient identification, uniqueness and existence theorems, boundary controllability, wave propagation in stratified media, viscous flows, nonlinear acoustics, Sobolev spaces, singularity theory, pseudo differential operators, and semigroup theory.
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US$ 195.85
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, SG, 2026
ISBN 10: 981982723X ISBN 13: 9789819827237
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physics, offering modern data-driven tools where traditional analytical and numerical methods fall short. As physical systems grow more complex or chaotic, deep learning provides efficient surrogates and physics-informed models capable of capturing dynamics and uncovering governing laws directly from data.This book introduces Neural ODEs, Physics-Informed Neural Networks (PINNs), and Hamiltonian and Lagrangian Neural Networks, showing how they enhance classical mechanics and PDE solvers for both forward and inverse problems. With Keras code examples, Google Colab notebooks, and practical exercises, this book serves researchers and students in physics, mathematics, and engineering seeking a concise, hands-on guide to applying deep learning in physical systems.
-
Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, 2026
ISBN 10: 981982723X ISBN 13: 9789819827237
US$ 271.88
US$ 16.74 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketHardcover. Condition: Brand New. 550 pages. 6.00x1.19x9.00 inches. In Stock.
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Deep Learning Methods Of Mathematical Physics - Volume I: Direct And Inverse Problems
Language: English
Published by World Scientific Publishing Co Pte Ltd, SG, 2026
ISBN 10: 981982723X ISBN 13: 9789819827237
US$ 224.32
US$ 87.04 shipping
Ships from United Kingdom to U.S.A.Quantity: 13 available
Add to basketHardback. Condition: New. This book explores how Artificial Intelligence and Deep Learning are transforming Mathematical Physics, offering modern data-driven tools where traditional analytical and numerical methods fall short. As physical systems grow more complex or chaotic, deep learning provides efficient surrogates and physics-informed models capable of capturing dynamics and uncovering governing laws directly from data.This book introduces Neural ODEs, Physics-Informed Neural Networks (PINNs), and Hamiltonian and Lagrangian Neural Networks, showing how they enhance classical mechanics and PDE solvers for both forward and inverse problems. With Keras code examples, Google Colab notebooks, and practical exercises, this book serves researchers and students in physics, mathematics, and engineering seeking a concise, hands-on guide to applying deep learning in physical systems.
-
Some direct and inverse problems of mathematical physics
Language: English
Published by LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 3659523178 ISBN 13: 9783659523175
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The problems of nonlocal type have been repeatedly studied earlier. The main principal property of these problems is their non-selfadjointness. It causes the main difficulties in their analytical and numerical solutions. Assuming strong singularity of boundary conditions of the problem, the well-posedness of its formulation can be proved by Fourier method of separation of variables. The problems, boundary conditions of which do not have the property of strong regularity are less studied. We have considered the question of existence of the regular and strong solution of a differential problem, its uniqueness and stability of initial data in various metrics. The monograph also deals with inverse problems. The monograph is intended for specialists in the field of differential equations and the theory of differential operators, doctoral students, as well as for undergraduates and senior students specializing in this field. And also can be used for drawing up of special courses on differential equations in higher educational institutions. 128 pp. Englisch.
