About the Editors |
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Part A Introduction to AI for Science |
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1 | (26) |
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3 | (10) |
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2 The AI for Science Book in a Nutshell |
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13 | (14) |
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27 | (152) |
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3 Data-Driven Science in the Era of AI: From Patterns to Practice |
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29 | (24) |
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4 AI in the Broader Context of Data Science |
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53 | (14) |
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5 AlphaFold --- The End of the Protein Folding Problem or the Start of Something Bigger? |
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67 | (14) |
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6 Applications of AI in Astronomy |
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81 | (14) |
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7 Machine Learning for Complex Instrument Design and Optimization |
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95 | (22) |
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8 Artificial Intelligence (AI) and Machine Learning (ML) at Experimental Facilities |
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117 | (28) |
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9 The First Exascale Supercomputer Accelerating Al-for-Science and Beyond |
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145 | (18) |
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10 Benchmarking for AI for Science |
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163 | (16) |
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Part C Exploring Application Domains |
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179 | (2) |
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181 | (38) |
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11 Radio Astronomy and the Square Kilometre Array |
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183 | (20) |
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12 AI for Astronomy: The Rise of the Machines |
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203 | (16) |
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219 | (50) |
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221 | (22) |
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14 AI for Climate Science |
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243 | (26) |
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269 | (34) |
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15 Accelerating Fusion Energy with AI |
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271 | (14) |
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16 Artificial Intelligence for a Resilient and Flexible Power Grid |
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285 | (18) |
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303 | (32) |
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17 AI and Machine Learning in Observing Earth from Space |
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305 | (14) |
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18 Artificial Intelligence in Plant and Agricultural Research |
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319 | (16) |
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335 | (44) |
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19 AI and Pathology: Steering Treatment and Predicting Outcomes |
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337 | (18) |
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20 The Role of Artificial Intelligence in Epidemiological Modeling |
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355 | (24) |
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379 | (32) |
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21 Big AI: Blending Big Data with Big Theory to Build Virtual Humans |
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381 | (18) |
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22 A Roadmap for Defining Machine Learning Standards in Life Sciences |
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399 | (12) |
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Materials Science and Engineering |
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411 | (34) |
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23 Artificial Intelligence for Materials |
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413 | (18) |
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24 Artificial Intelligence for Accelerating Materials Discovery |
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431 | (14) |
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445 | (48) |
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25 Experimental Particle Physics and Artificial Intelligence |
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447 | (18) |
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26 AI and Theoretical Particle Physics |
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465 | (28) |
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Part D The Ecosystem of AI for Science |
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493 | (148) |
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27 Schema.org for Scientific Data |
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495 | (20) |
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28 Al-coupled HPC Workflows |
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515 | (20) |
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29 AI for Scientific Visualization |
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535 | (18) |
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30 Uncertainty Quantification in AI for Science |
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553 | (18) |
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31 AI for Next-Generation Global Network-Integrated Systems and Testbeds |
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571 | (38) |
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32 AI for Optimal Experimental Design and Decision-Making |
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609 | (18) |
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33 FAIR: Making Data AI-Ready |
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627 | (14) |
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Part E Perspectives on AI for Science |
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641 | (82) |
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34 Large Language Models for Science |
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643 | (28) |
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35 AI for Autonomous Vehicles |
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671 | (8) |
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36 The Automated AI-driven Future of Scientific Discovery |
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679 | (14) |
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37 Towards Reflection Competencies in Intelligent Systems for Science |
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693 | (14) |
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38 The Interface of Machine Learning and Causal Inference |
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707 | (16) |
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Part F Endpiece: AI Tools and Concepts |
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723 | (44) |
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39 Overview of Deep Learning and Machine Learning |
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725 | (18) |
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40 Topics, Concepts, and AI Methods Discussed in Chapters |
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743 | (24) |
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Index |
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767 | |