ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS
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.
"1138595554"
ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS
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.
118.99 In Stock
ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS

ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS

ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS

ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS

eBook

$118.99  $158.00 Save 25% Current price is $118.99, Original price is $158. You Save 25%.

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers


Overview

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.

Product Details

ISBN-13: 9789811234040
Publisher: World Scientific Publishing Company, Incorporated
Publication date: 01/05/2022
Series: 0
Sold by: Barnes & Noble
Format: eBook
Pages: 828
File size: 24 MB
Note: This product may take a few minutes to download.
From the B&N Reads Blog

Customer Reviews