IML Machine Learning Working Group: Theory applications of ML

Friday 16 Jun 2017, 15:00 → 17:45 Europe/Zurich

222/R-001 (CERN)

Agenda under development. If you like to present, please contact iml.coordinators@cern.ch

15:00 → 15:10 News and group updates

Speakers: Lorenzo Moneta (CERN), Michele Floris (CERN), Paul Seyfert (Universita & INFN, Milano-Bicocca (IT)), Dr Sergei Gleyzer (University of Florida (US)), Steven Randolph Schramm (Universite de Geneve (CH))

IML_Sergei_Gleyzer_News_06162017.pdf

IML_Sergei_Gleyzer_News_06162017.pptx

15:10 → 15:20 Machine learning knowledge base

Speaker: Matthew Feickert (Southern Methodist University (US))

Feickert_2017-06-16.pdf

HEPML Resources GitHub Repo

15:20 → 15:40 Deep learning for Phase-Space Integration

Speaker: Josh Bendavid (California Institute of Technology (US))

mlmc-Jun16-2017.pdf

15:40 → 16:00 Machine Learning for Phenomenological Models

Speaker: Bob Stienen

20170616_IML.pdf

16:00 → 16:20 Learning parton densities with neural networks: The NNPDF methodology

Speaker: Zahari Dimitrov Kassabov Zaharieva (Universita e INFN Torino (IT))

talk.pdf

16:20 → 16:40 Machine Learning of Calabi-Yau Volumes

Speaker: Daniel Krefl (CERN)

CERN June 17 - ML meeting.pdf

16:40 → 17:00 An EoS-meter of QCD transition from deep learning

Speaker: Dr Long-Gang Pang (Frankfurt Institute for Advanced Studies, Goethe University)

EoS_Deep_Learning_for_CERN.key

EoS_Deep_Learning_for_CERN.pdf

17:00 → 17:01 Minutes

IML-2017-06-16-minutes.txt