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Special Topics

EPJ ST Special Issue: Modern machine learning and particle physics: An in-depth review

Over the past few years, machine learning has been revolutionizing particle physics. Modern machine learning techniques, including deep learning, are rapidly being applied, adapted, and developed for high energy physics. This EPJ ST special issue will feature some articles which will review some aspects of the natural synergy between machine learning and theoretical and experimental particle physics. The editors of this special issue attempt to bring in contributions from enthusiastic and highly active researchers. Several expert theorists and experimentalists have already agreed to contribute to this collection. Should you wish to contribute, please write to the Guest Editors Biplob Bhattacherjee and Swagata Mukherjee to see how your contribution may fit into the collection.

Guest Editors:

Prof. B. Bhattacherjee, Centre for High Energy Physics, Indian Institute of Science, Bangalore 560 012, India, This email address is being protected from spambots. You need JavaScript enabled to view it.

Dr. Swagata Mukherjee, Department of Physics, Indian Institute of Technology, Kanpur, 208016, India, This email address is being protected from spambots. You need JavaScript enabled to view it.

Managing Editors
Anne Ruimy and Vijala Kiruvanayagam (EDP Sciences) and Sabine Lehr (Springer-Verlag)
Dear Sabine,
On this occasion, may I also thank you for your support: collaboration with you is always very pleasant and effective. Have a nice day, yours, Yurij

Yurij Holovatch, National Academy of Sciences, Lviv, Ukraine
Editor EPJ Special Topics 216, 2013

ISSN: 1951-6355 (Print Edition)
ISSN: 1951-6401 (Electronic Edition)

© EDP Sciences and Springer-Verlag