Scientific Machine Learning

Chapter 1. Domain-decomposed image classification algorithms using linear discriminant analysis and convolutional neural networks.- Chapter 2. Discovering Partially Known Ordinary Differential Equations: a Case Study on the Chemical Kinetics of Cellulose Degradation.- Chapter 3. Deep Unfolding for Scientific Computing on Embedded Systems.- Chapter 4. Non-Asymptotic Analysis of Projected Gradient Descent for Physics-Informed Neural Networks.- Chapter 5. MILP Initialization for Power Transformer Dynamic Thermal Modeling with PINNs.- Chapter 6. 3D point cloud generation for surface representation.- Chapter 7. Generative Models for Parameter Space Reduction applied to Reduced Order Modelling.- Chapter 8. High-Fidelity Description of Platelet Deformation Using a Neural Operator.- Chapter 9. Nonlinear reduction strategies for data compression: a comprehensive comparison from Diffusion to Advection problems.- Chapter 10. Model Reduction for Transport-Dominated Problems via Cross-Correlation Based Snapshot Registration.

• Erscheinungsdatum: 23.02.2026
• Autor/Autorin: Federico Pichi
• Reihe: Springer Nature Proceedings excluding Computer Science
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 36.1 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 218 Seiten
• ISBN: 9783032115270
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.