图书简介

Contributing Authors: AI for Science (Alok Choudhary, Geoffrey Fox, and Tony Hey); Overview of the Book; Setting the Scene: Data Driven Science in the Era of AI: From Patterns to Practice (Alex Szalay); AI in the Broader Context of Data Science(Rafael Alvarado and Philip Bourne); AlphaFold — The End of the Protein Folding Problem or the Start of Something Bigger? (David T Jones and Janet M Thornton); Applications of AI in Astronomy (S G Djorgovski, A A Mahabal, M J Graham, K Polsterer, and A Krone-Martins); Machine Learning for Complex Instrument Design and Optimization (Barry C Barish, Jonathan Richardson, Evangelos Papalexakis, and Rutuja Gurav); Artificial Intelligence (AI) and Machine Learning (ML) at Experimental Facilities (JA Sethian, JJ Donatelli, A Hexemer, MM Noack, DM Pelt, DM Ushizima, and PH Zwart); The First Exascale Supercomputer: Accelerating AI-for-Science and Beyond (Satoshi Matsuoka, Mohamed Wahib, Aleksandr Drozd, and Kento Sato); Benchmarking for AI for Science (Jeyan Thiyagalingam, Mallikarjun Shankar, Geoffrey Fox, and Tony Hey); Exploring Application Domains: Astronomy and Cosmology: Radio Astronomy and the Square Kilometre Array (Anna Scaife); AI for Astronomy: The Rise of the Machines (Andy Connolly); Climate Change: AI and Net Zero (Alberto Arribas, Karin Strauss, Sharon Gillett, Amy Luers, Trevor Dhu, Lucas Joppa, Roy Zimmermann, and Vanessa Miller); AI for Climate Science (Philip Stier); Energy: Accelerating Fusion Energy with AI (Steve Cowley, Dan Boyer, and Michael Churchill); Artificial Intelligence for a Resilient and Flexible Power Grid (Olufemi A Omitaomu, Jin Dong, and Teja Kuruganti); Environmental Science: AI and Machine Learning in Observing Earth from Space (Jeff Dozier); Artificial Intelligence in Plant and Agricultural Research (Sabina Leonelli and Hugh F Williamson); Health: AI and Pathology: Steering Treatment and Predicting Outcomes (Rajarsi Gupta, Jakub Kaczmarzyk, Soma Kobayashi, Tahsin Kurc, and Joel Saltz); The Role of Artificial Intelligence in Epidemiological Modeling (Madhav V Marathe et al.); Life Sciences: Big AI: Blending Big Data With Big Theory to Build Virtual Humans (Peter Coveney and Roger Highfield); A Roadmap for Defining Machine Learning Standards in the Life Sciences (Fotis Psomopoulos, Carole Goble, Leyla Jael Castro, Jennifer Harrow, and Silvio C E Tosatto); Materials Science and Engineering: Artificial Intelligence for Materials (Debra J Audus, Kamal Choudhary, Brian L DeCost, A Gilad Kusne, Francesca Tavazza, and James A Warren); Artificial Intelligence for Accelerating Materials Discovery (Ankit Agrawal and Alok Choudhary); Particle Physics: Experimental Particle Physics and Artificial Intelligence (David Rousseau); AI and Theoretical Particle Physics (Rajan Gupta, Tanmoy Bhattacharya, and Boram Yoon); The Ecosystem of AI for Science: Schemaorg for Scientific Data (Alasdair Gray, Leyla Castro, Nick Juty and Carole Goble); AI-enabled HPC Workflows (Shantenu Jha, Vincent Pascuzzi, and Matteo Turilli); AI for Scientific Visualization (Han-Wei Shen and Chris Johnson); Uncertainty Quantification in AI for Science (Tanmoy Bhattacharya, Christina Garcia Cardona, and Jamal Mohd-Yusof); AI for Next Generation Global Network-Integrated Systems and Testbeds (Mariam Kiran and Harvey Newman); AI for Optimal Experimental Design and Decision Making (Francis J Alexander, Kristofer-Roy Reyes, Lav R Varshney, and Byung-Jun Yoon); FAIR: Making Data AI-Ready (Susanna-Assunta Sansone, Lee Harland, Philippe Rocca-Serra, and Mark Wilkinson); Perspectives on AI for Science: Large Language Models for Science (Austin Clyde, Arvind Ramanathan, and Rick Stevens); AI for Autonomous Vehicles (Tom St John and Vijay Janapa Reddi); The Automated AI-Drive Future of Scientific Discovery (Ross King and Hector Zenil); Towards Reflection Competencies in Intelligent Systems for Science (Yolanda Gil); The Interface of Machine Learning and Causal Inference (Mohammad Taha Bahadori and David Heckerman); Endpiece: AI Tools and Concepts: Survey of Deep Learning Methods; AI Methods Discussed in Chapters;

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