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Discovery in Physics

Volume 2 covers knowledge discovery in particle and astroparticle physics. Instruments gather petabytes of data and machine learning is used to process the vast amounts of data and to detect relevant examples efficiently. The physical knowledge is encoded in simulations used to train the machine lea...

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Bibliographic Details
Main Author: Morik, Katharina
Other Authors: Rhode, Wolfgang
Format: eBook
Language:English
Published: Berlin/Boston De Gruyter 2022
Series:De Gruyter STEM
Subjects:
Resource-aware Machine Learning
Machine Learning In High-energy Physics
Computer Networking And Communications / Bicssc
Thema Editeur::p Mathematics And Science::pn Chemistry
Big Data And Machine Learning
Software Cyber-physical Systems
Thema Editeur::u Computing And Information Technology::um Computer Programming / Software Engineering::umb Algorithms And Data Structures
Resource-constrained Data Analysis
Ml On Small Devices Data Mining For Ubiquitous System
Algorithms And Data Structures / Bicssc
Embedded Systems And Machine Learning
Artificial Intelligence / Bicssc
Thema Editeur::u Computing And Information Technology::un Databases
Artificial Intelligence
Machine Learning For Knowledge Discovery
Thema Editeur::u Computing And Information Technology::uy Computer Science::uyq Artificial Intelligence
Databases / Bicssc
Highly Distributed Data
Thema Editeur::u Computing And Information Technology::ut Computer Networking And Communications
Chemistry / Bicssc
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:Volume 2 covers knowledge discovery in particle and astroparticle physics. Instruments gather petabytes of data and machine learning is used to process the vast amounts of data and to detect relevant examples efficiently. The physical knowledge is encoded in simulations used to train the machine learning models. The interpretation of the learned models serves to expand the physical knowledge resulting in a cycle of theory enhancement.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (349 p.)
ISBN:9783110786132
9783110785968
9783110785951

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