Название: Artificial Intelligence for High Energy Physics Автор: Editors Paolo Calafiura, David Rousseau, Kazuhiro Terao Издательство: World Scientific Publishing Год: 2022 Страниц: 829 Размер: 66.29 МБ Формат: PDF Язык: English
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.
Physics of Data Science and Machine Learning Название: Physics of Data Science and Machine Learning Автор: Ijaz A. Rauf Издательство: CRC Press Год: 2022 Страниц: 211 Язык: английский Формат:...
A Closer Look at Big Data Analytics Название: A Closer Look at Big Data Analytics Автор: R. Anandan Издательство: Nova Science Publishers, Inc. Год: 2021 Страниц: 378 Язык: английский...
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Artificial Intelligence for High Energy Physics 
