Stochastic dynamics continuous time methods de wang guangyu (2 resultados)

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  • Idioma: Inglés

    Editorial: BestAI Press, 2026

    9798907070073

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    Condición: Nuevo

    EUR 39,69

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    Cantidad disponible: Más de 20 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Amazon Digital Services LLC - Kdp Aug 2026, 2026

    9798907070073

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 58,53

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    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. Neuware - Continuous-time mathematics has become a common language across modern artificial intelligence. Yet the same words-gradient flow, diffusion, entropy, sampling, control, and equilibrium-often refer to different mathematical objects, metrics, and regimes. This book is built around making those distinctions precise. Stochastic Dynamics for AI develops deterministic and stochastic dynamics from first principles and then uses them to connect Fokker-Planck equations and Wasserstein gradient flows; diffusion and flow-based generative models; Langevin, Hamiltonian, and non-reversible sampling; particle and variational inference; stochastic-gradient dynamics and the edge of stability; entropy-regularized control and continuous-time reinforcement learning; mean-field limits and games; and path-space relative entropy and Schrödinger bridges. Rather than presenting these subjects as isolated toolkits, the book asks a harder question: when does an idea transfer from one domain to another Each major connection is separated into what is exact, what requires a limiting argument or a change of representation, and what fails outside its stated assumptions. Scope boxes, counterexamples, comparison tables, and four tiers of exercises make the hypotheses-and the boundaries of the conclusions-part of the mathematics. Designed for advanced undergraduates, graduate students, and researchers in mathematics, statistics, machine learning, and related fields, this volume offers a rigorous guide to the continuous-time structures that underlie learning, generation, sampling, optimization, control, and interacting AI systems.…