Chapter 40: Topics, Concepts, and AI Methods Discussed in Chapters
The following sections are included:
Overview
Chapter 3. Data-Driven Science in the Era of AI: From Patterns to Practice
Chapter 4. AI in the Broader Context of Data Science
Chapter 5. AlphaFold — The End of the Protein Folding Problem or the Start of Something Bigger?
Chapter 6. Applications of AI in Astronomy
Chapter 7. Machine Learning for Complex Instrument Design and Optimization
Chapter 8. Artificial Intelligence (AI) and Machine Learning (ML) at Experimental Facilities
Chapter 9. The First Exascale Supercomputer: Accelerating AI-for-Science and Beyond
Chapter 10. Benchmarking for AI for Science
Chapter 11. Radio Astronomy and the Square Kilometer Array
Chapter 12. The Rise of the Machines
Chapter 13. AI for Net-Zero
Chapter 14. AI for Climate Science
Chapter 15. Accelerating Fusion Energy with AI
Chapter 16. Artificial Intelligence for a Resilient and Flexible Power Grid
Chapter 17. AI and Machine Learning in Observing Earth from Space
Chapter 18. Artificial Intelligence in Plant and Agricultural Research
Chapter 19. AI and Pathology: Steering Treatment and Predicting Outcomes
Chapter 20. The Role of Artificial Intelligence in Epidemiological Modeling
Chapter 21. Big AI: Blending Big Data with Big Theory to Build Virtual Humans
Chapter 22. A Roadmap for Defining Machine Learning Standards in Life Sciences
Chapter 23. Artificial Intelligence for Materials
Chapter 24. Artificial Intelligence for Accelerating Materials Discovery
Chapter 25. Experimental Particle Physics and Artificial Intelligence
Chapter 26. AI and Theoretical Particle Physics
Chapter 27. Schema.org for Scientific Data
Chapter 28. AI-Enabled HPC Workflows
Chapter 29. AI for Scientific Visualization
Chapter 30. Uncertainty Quantification in AI for Science
Chapter 31. AI for Next-Generation Global Network-Integrated Systems and Testbeds
Chapter 32. AI for Optimal Experimental Design and Decision-Making
Chapter 33. FAIR: Making Data AI-Ready
Chapter 34. Large Language Models for Science
Chapter 35. Autonomous Vehicles
Chapter 36. The Automated AI-Driven Future of Scientific Discovery
Chapter 37. Towards Reflection Competencies in Intelligent Systems for Science
Chapter 38. The Interface of Machine Learning and Causal Inference