Variational and Information Flows in Machine Learning and Optimal Transport
This book is based on lectures given at the Mathematisches Forschungsinstitut Oberwolfach on “Computational Variational Flows in Machine Learning and Optimal Transport”. Variational and stochastic flows on measure spaces are ubiquitous in machine learning and generative modeling. Optimal transport a...
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| Autors principals: | , , , , |
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| Autor corporatiu: | |
| Format: | Electrònic eBook |
| Idioma: | anglès |
| Publicat: |
Cham :
Springer Nature Switzerland : Imprint: Birkhäuser,
2025.
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| Edició: | 1st ed. 2025. |
| Col·lecció: | Oberwolfach Seminars,
56 |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/978-3-031-92731-7 |
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Taula de continguts:
- - 1. A Dynamic Perspective of Optimal Transport
- 2. A Geometric Perspective on Diffeomorphic and Optimal Transport Flows and Their Applications
- 3. Wasserstein Dynamics in Mathematical Data Sciences
- 4. Flow Matching: Markov Kernels, Stochastic Processes and Transport Plans.