Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students
Machine learning is an important applied research area in particle physics, beginning with applicati...
Machine learning is an important applied research area in particle physics, beginning with applicati...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
This concise set of course-based notes provides the reader with the main concepts and tools needed t...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
International audienceThe Higgs boson discovery at the Large Hadron Collider in 2012 relied on boost...
In these proceedings we perform a brief review of machine learning (ML) applications in theoretical ...
Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses o...
These lectures cover the basic ideas of frequentist and Bayesian analysis and introduce the mathemat...
This thesis studies the performance of statistical learning methods in high energy and astrophysics...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
This document introduces basics in data preparation, feature selection and learning basics for high ...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
Machine learning is an important applied research area in particle physics, beginning with applicati...
Machine learning is an important applied research area in particle physics, beginning with applicati...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
This concise set of course-based notes provides the reader with the main concepts and tools needed t...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
The lectures will cover multivariate statistical methods and their applications in High Energy Physi...
International audienceThe Higgs boson discovery at the Large Hadron Collider in 2012 relied on boost...
In these proceedings we perform a brief review of machine learning (ML) applications in theoretical ...
Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses o...
These lectures cover the basic ideas of frequentist and Bayesian analysis and introduce the mathemat...
This thesis studies the performance of statistical learning methods in high energy and astrophysics...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
This document introduces basics in data preparation, feature selection and learning basics for high ...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...
Machine learning is an important applied research area in particle physics, beginning with applicati...
Machine learning is an important applied research area in particle physics, beginning with applicati...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will ...