Physics-Based Deep Learning
Overview & Synopsis
This book contains a practical and comprehensive introduction of everything related to deep learning in the context of physical simulations, focuses on physical loss constraints, more tightly coupled learning algorithms with differentiable simulations, training algorithms tailored to physics problems, as well as reinforcement learning and uncertainty modeling.
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Document Information
| Document Title | Physics-Based Deep Learning |
|---|---|
| Author / Organization | Nils Thuerey, Philipp Holl, Maximilian Mueller, Patrick Schnell, Felix Trost, Kiwon Um |
| Subject & Discipline | Deep Learning and Neural Networks, Physics, Computational Physics, and Mathematical Physics, Machine Learning, Data Science, Data Analysis and Data Mining |
| Categories | Deep Learning and Neural Networks |
| License / Rights | Creative Commons License (CC) |
| Resource Verification | Verification pending |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Language | ENGLISH |
| Catalog ID | DOC-93342 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |