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Computational Science - ICCS 2025 Workshops

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Computational Science - ICCS 2025 Workshops: 25th International Conference, Singapore, Singapore, July 7-9, 2025, Proceedings, Part I (Lecture Notes in Computer Science) by Maciej Paszynski, Amanda S. Barnard, Yongjie Jessica Zhang
English | July 7, 2025 | ISBN: 3031975537 | 476 pages | EPUB | 64 Mb
The 6-volume set constitutes the workshop proceedings of the 25th International Conference on Computational Science, ICCS 2025, which took place in Singapore, Singapore, during July 7-9, 2025.​

The 137 full papers and 32 short papers presented in these proceedings were carefully reviewed and selected from 322 submissions. The papers are organized in the following topical sections:
Volume I:
Advances in high-performance computational earth sciences: numerical methods, frameworks & applications; artificial intelligence approaches for network analysis; artificial intelligence and high-performance computing for advanced simulations; and biomedical and bioinformatics challenges for computer science.
Volume II:
Computational health; computational modeling and artificial intelligence for social systems; and computational optimization, modelling and simulation.
Volume III:
Computational science and AI for addressing complex and dynamic societal challenges equitably; computer graphics, image processing and artificial intelligence; computing and data science for materials discovery and design; and large language models and intelligent decision-making within the digital economy.
Volume IV:
Machine learning and data assimilation for dynamical systems; and multi-criteria decision-making: methods, applications, and innovations.
Volume V:
(Credible) Multiscale modelling and simulation; numerical algorithms and computer arithmetic for computational science; quantum computing; retrieval-augmented generation; and simulations of flow and transport: modeling, algorithms and computation.
Volume VI:
Smart systems: bringing together computer vision, sensor networks and artificial intelligence; solving problems with uncertainty; and teaching computational science.


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