Generative AI and Stochastic Thermodynamics: A Tale of Free Energies - Softcover

Welling, Max ; Lu, Sirui ; Holdijk, Lars

9781009709033: Generative AI and Stochastic Thermodynamics: A Tale of Free Energies

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ISBN 10: 1009709038 ISBN 13: 9781009709033

Verlag: Cambridge University Press, 2026

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A timely text providing a unifying perspective on the mathematics of generative AI and stochastic thermodynamics.

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�ber die Autorin bzw. den Autor

Max Welling is the co-founder and Chief Technology Officer of the startup CuspAI, and a Full Professor of Machine Learning at the University of Amsterdam. He is a member of the Dutch Royal Academy of Sciences and the Canadian Institute for Advanced Research, and a fellow of the European Lab for Learning and Intelligent Systems. Professor Welling received the ECCV Koenderink Prize in 2010, the 2021 ICML Test of Time Award, and the 2024 ICLR Test of Time Award.

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Verlag: Cambridge University Press
Erscheinungsdatum: 2026
Sprache: Englisch
ISBN 10: 1009709038
ISBN 13: 9781009709033
Einband: Taschenbuch
Anzahl der Seiten: 314
Kontakt zum Hersteller: Cambridge University Press
https://www.cambridge.org/

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Generative AI and Stochastic Thermodynamics (Paperback or Softback)

Welling, Max

Verlag: Cambridge University Press 8/20/2026, 2026

ISBN 10: 1009709038 ISBN 13: 9781009709033

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Paperback or Softback. Zustand: New. Generative AI and Stochastic Thermodynamics. Book. Bestandsnummer des Verk�ufers BBS-9781009709033

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Generative AI and Stochastic Thermodynamics

Welling, Max

Verlag: Cambridge University Press, 2026

ISBN 10: 1009709038 ISBN 13: 9781009709033

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Generative AI and Stochastic Thermodynamics (Paperback)

Max Welling

Verlag: Cambridge University Press, Cambridge, 2026

ISBN 10: 1009709038 ISBN 13: 9781009709033

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Paperback. Zustand: new. Paperback. Originating from lectures delivered at the African Institute of Mathematical Sciences, this book presents a unifying perspective on traditional and modern methods in generative AI and stochastic thermodynamics. By relating the core topics in machine learning to the notion of (variational) free-energy, a bridge is built between methods such as latent variable models, variational auto-encoders, optimal control, optimal transport, normalizing flows and diffusion models and concepts such as entropy production and fluctuation theorems in stochastic thermodynamics. Structured into three main parts, the book commences by setting up the required mathematical and statistical physics preliminaries needed to make it broadly accessible. The largest part of the book then focuses on building intuition of major advances in generative AI by considering discrete time processes and their relationship to topics in stochastic thermodynamics. Finally, the authors take a short excursion to the continuous time domain for the more advanced learner. Bridging the gap between stochastic thermodynamics and generative AI, this book will interest those working in either discipline, as well as physicists hoping to enter the field of AI. It covers the fundamental concepts before progressing to more advanced methods and encourages the reader to build their intuition. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verk�ufers 9781009709033

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Generative AI and Stochastic Thermodynamics

Lars Holdijk, Max Welling, Sirui Lu

Verlag: Cambridge University Press, GB, 2026

ISBN 10: 1009709038 ISBN 13: 9781009709033

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Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes K�nigreich

Verk�uferbewertung 5 von 5 Sternen

Paperback. Zustand: New. Originating from lectures delivered at the African Institute of Mathematical Sciences, this book presents a unifying perspective on traditional and modern methods in generative AI and stochastic thermodynamics. By relating the core topics in machine learning to the notion of (variational) free-energy, a bridge is built between methods such as latent variable models, variational auto-encoders, optimal control, optimal transport, normalizing flows and diffusion models and concepts such as entropy production and fluctuation theorems in stochastic thermodynamics. Structured into three main parts, the book commences by setting up the required mathematical and statistical physics preliminaries needed to make it broadly accessible. The largest part of the book then focuses on building intuition of major advances in generative AI by considering discrete time processes and their relationship to topics in stochastic thermodynamics. Finally, the authors take a short excursion to the continuous time domain for the more advanced learner. Bestandsnummer des Verk�ufers LU-9781009709033

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