Machine Learning for Jet Physics

Name: Machine Learning for Jet Physics
Start: 2017-12-11T01:15:00-08:00
End: 2017-12-13T18:00:00-08:00
Location: Lawrence Berkeley National Laboratory

11–13 Dec 2017

Lawrence Berkeley National Laboratory

US/Pacific timezone

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.

Starts 11 Dec 2017, 01:15

Ends 13 Dec 2017, 18:00

US/Pacific

Lawrence Berkeley National Laboratory

2-100

Benjamin Nachman
Kyle Cranmer
Matt Dolan
Timothy Cohen

Slides

ML4JP_Workshop_Directions_BreakoutRoom.pdf

ML4JP_Workshop_Directions.pdf

There is no fee for attending the workshop. Coffee and light refreshments will be provided during breaks but meals and lodging are the responsibility of the attendant. There are many hotels in the Berkeley area, including limited availability at the LBNL guesthouse (5 min walk from the workshop, $140/night). A complementary shuttle runs every 10 min from downtown Berkeley up to the lab. For lunches, the most convenient option will be to eat in the LBNL cafeteria (5 min walk from workshop, ~10$). Related workshops: DS@HEP: https://indico.fnal.gov/conferenceDisplay.py?ovw=True&amp;amp;confId=13497 BOOST: https://indico.cern.ch/event/579660/