| Artificial Intelligence for High Energy Physics Contributor(s): Calafiura, Paolo (Editor), Rousseau, David (Editor), Terao, Kazuhiro (Editor) |
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ISBN: 9811234027 ISBN-13: 9789811234026 Publisher: World Scientific Publishing Company OUR PRICE: $188.10 Product Type: Hardcover Published: March 2022 |
| Additional Information |
| BISAC Categories: - Science | Physics - Nuclear - Computers | Neural Networks |
| Physical Information: 1.2" H x 5.9" W x 9.1" (2.30 lbs) 828 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: The Higgs boson discovery at the Large Hadron Collider in 2012 relied on boosted decision trees. Since then, high energy physics (HEP) has applied modern machine learning (ML) techniques to all stages of the data analysis pipeline, from raw data processing to statistical analysis. The unique requirements of HEP data analysis, the availability of high-quality simulators, the complexity of the data structures (which rarely are image-like), the control of uncertainties expected from scientific measurements, and the exabyte-scale datasets require the development of HEP-specific ML techniques. While these developments proceed at full speed along many paths, the nineteen reviews in this book offer a self-contained, pedagogical introduction to ML models' real-life applications in HEP, written by some of the foremost experts in their area. |