Machine Learning for Jet Physics

US/Pacific
2-100 (Lawrence Berkeley National Laboratory)

2-100

Lawrence Berkeley National Laboratory

Benjamin Nachman, Kyle Cranmer, Matt Dolan, Timothy Cohen (Princeton/IAS)
Description
There has been a recent surge of interest in developing and applying advanced machine learning techniques in HEP, and jet physics is a domain at the forefront of the excitement. The goal of this workshop is to gather experts and new-commers to discuss progress, new ideas, and common challenges. The workshop is open to the community; we invite contributions and will try to accommodate everyone within reason.
Slides
Participants
  • Anders Andreassen
  • Andrew Larkoski
  • Aviv Cukierman
  • Benjamin Nachman
  • Bryan Ostdiek
  • Charilou Labitan
  • Christine McLean
  • Christopher Frye
  • Eric Metodiev
  • Felix Ringer
  • Francesco Rubbo
  • Frederic Dreyer
  • Gabriela Lima Lichtenstein
  • Gregor Kasieczka
  • Huilin Qu
  • Ian Moult
  • Isaac Henrion
  • Jack Collins
  • Jannicke Pearkes
  • Kiel Howe
  • Kyle Cranmer
  • LongGang Pang
  • Luke de Oliveira
  • Maosen Zhou
  • Marat Freytsis
  • Markus Stoye
  • Matthew Dolan
  • Matthew Schwartz
  • Michael Kagan
  • Michela Paganini
  • Patrick Komiske
  • Peter Jacobs
  • Peter Sadowski
  • Raghav Kunnawalkam Elayavalli
  • Rebecca Carney
  • Rohan Bhandari
  • Sai Neha Santpur
  • Savannah Thais
  • Stefan Hoche
  • Steve Farrell
  • Taoli Cheng
  • Taylor Childers
  • Tilman Plehn
  • Tim Cohen
  • Wahid Bhimji
  • Wes Bethel
  • William Mccormack
  • Wojciech Fedorko
  • Yang-Ting Chien