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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Scientific Machine Learning: Emerging Topics

Scientific Machine Learning: Emerging Topics

Rozza, Gianluigi
Pichi, Federico
Strazzullo, Maria

Hardcover

Series: Sema Simai Springer, Book 42

General ComputersGeneral MathematicsProbability & Statistics

ISBN10: 3032115264
ISBN13: 9783032115263
Publisher: Springer
Published: Feb 24 2026
Pages: 218
Weight: 1.15
Height: 0.64 Width: 6.47 Depth: 9.34
Language: English
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.

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