Scientific Machine Learning

Language: English

Published by Springer, Springer International Publishing Feb 2026, 2026

3032115264 / 9783032115263

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This item is printed on demand - Print on Demand Titel. Neuware -This volume gathers peer-reviewed papers from the workshop Scientific Machine Learning: Emerging Topics, held at SISSA in Trieste, Italy. The event gathered leading researchers in mathematics, algorithms, and machine learning. Its goal was to advance the synergy between data-driven models and scientific computing, promoting robust, interpretable, and scalable methods. The works reflect major trends in scientific machine learning (SciML), including optimization, physics-informed learning, neural graph/operators/ODE, transformers, and generative models. Contributions propose physics-based constrained neural networks, advancements in optimization and model reduction, and applications across power systems, chemical kinetics, and biomechanics. Topics span from hybrid models for image classification to generative compression and neural operators for high-dimensional systems. Blending theory and practice, the volume captures the diversity and innovation shaping modern SciML.This volume is addressed to researchers and will provide readers with insight into the current state of the field, sparks new ideas, and encourages further research at the rich intersection of machine learning, mathematics, and scientific computing.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch.…

Seller Inventory # 9783032115263

Title
Scientific Machine Learning
Author
Federico Pichi
Publisher
Springer, Springer International Publishing Feb 2026
Publication year
2026
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3032115264
ISBN 13
9783032115263
Item weight
551 grams
Dimensions
241x160x18 mm

buchversandmimpf2000

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