Computational Science – ICCS 2020
20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part VII
João Teixeira editor Valeria V Krzhizhanovskaya editor Jack J Dongarra editor Peter M A Sloot editor Gábor Závodszky editor Michael H Lees editor Sérgio Brissos editor
Format:Paperback
Publisher:Springer Nature Switzerland AG
Published:20th Jun '20
Currently unavailable, and unfortunately no date known when it will be back
The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.*
The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named:
Part I: ICCS Main Track
Part II: ICCS Main Track
Part III: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Agent-Based Simulations, Adaptive Algorithms and Solvers; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Biomedical and Bioinformatics Challenges for Computer Science
Part IV: Classifier Learning from Difficult Data; Complex Social Systems through the Lens of Computational Science; Computational Health; Computational Methods for Emerging Problems in (Dis-)Information Analysis
Part V: Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems; Computer Graphics, Image Processing and Artificial Intelligence
Part VI: Data Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; Meshfree Methods in Computational Sciences; Multiscale Modelling and Simulation; Quantum Computing Workshop
Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainties; Teaching Computational Science; UNcErtainty QUantIficatiOn for ComputationAl modeLs
*The conference was canceled due to the COVID-19 pandemic.Chapter ‘APE: A Command-Line Tool and API for Automated Workflow Composition’ is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
ISBN: 9783030504359
Dimensions: unknown
Weight: unknown
775 pages
1st ed. 2020