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 ...
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... Google Books
Originally published: 2022
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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 ...
Modern machine learning techniques, including deep learning, is rapidly being applied, adapted, and developed for high energy physics. The goal of this document ...
Jun 5, 2024 · High-energy physics can trace its relationship with machine learning back many decades, with the earliest neural networks coming into play ...
Nov 29, 2022 · The US Department of Energy (DOE) announced $4.3 million in funding for 16 projects in artificial intelligence (AI) research for high energy physics (HEP).
Particle physicists have devised new AI techniques to help them classify the mass of complex data generated by the ATLAS experiment at the Large Hadron Collider ...
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The goal of this school is to provide hands-on training on cutting edge machine learning methods in HEP by combining extensive advanced courses taught with ...
Symmetry's guide to AI in particle physics and astrophysics
www.symmetrymagazine.org › article › s...
Apr 17, 2024 · Symmetry will explore the ways scientists are using artificial intelligence to advance particle physics and astrophysics—in a series of articles ...
AI techniques applied to physics can enhance our understanding the basic components of matter, help reveal the nature of space and time, and enable the ...
This paper explores the transformative potential of artificial intelligence (AI) in the field of physics, emphasizing the application of machine learning (ML) ...
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