Description
The goal of this workshop is to bring together members of the community from the academic and private sector that are interested in a combination of machine learning and energy landscapes, with emphasis on, but not limited to, the energy landscape of string theory. The program will feature plenary sessions as well as shorter, more specialized talks and time for discussions to explore synergies between these different approaches.
Go to day
  • Monday, 10 December 2018
    • 08:30 - 16:00
      • 08:30 Registration formalities 30' ( Adriatico Guest House - Kastler Lecture Hall Area (Lower Level 1) )
      • 09:00 Complexity of Machine Learning and Landscapes 45'
        Speaker: James HALVERSON (Northeastern Univ.)
        Material: Slides Video
      • 09:45 Learning to Reheat with Random Matrix Theory 45'
        Speaker: Cody LONG (Northeastern Univ.)
        Material: Slides Video
      • 10:30 Coffee Break 30'
      • 11:00 Deep Learning and Holographic QCD 45'
        Speaker: Koji HASHIMOTO (Osaka Univ.)
        Material: Slides Video
      • 11:45 Learning to inflate 45'
        Speaker: Tom RUDELIUS (Institute for Advanced Study)
        Material: Slides Video
      • 12:30 Lunch Break 1h30' ( Adriatico Guest House - Cafeteria )
      • 14:00 Random Matrix Theory for Big-Data and Machine Learning 45'
        Speaker: Mohamed El Amine SEDDIK (CEA List)
        Material: Slides Video
      • 14:45 Machine learning for bounce calculation 45'
        Speaker: Ryusuke JINNO (IBS-CTPU)
        Material: Slides Video
      • 15:30 Coffee Break 30'
  • Tuesday, 11 December 2018
    • 09:00 - 21:00
      • 09:00 F-theory landscape with SCFT sectors 45'
        Speaker: Yinan WANG (University of Oxford)
        Material: Slides Video
      • 09:45 What do we need machine learning for? 45'
        Speaker: Alon FARAGGI (University of Liverpool)
        Material: Slides Video
      • 10:30 Coffee Break 30'
      • 11:00 Genetic Algorithms as a search tool for the string landscape  45'
        Speaker: Steve ABEL (Durham University)
        Material: Slides Video
      • 11:45 Deep learning in the heterotic orbifold landscape 45'
        Speaker: Patrick VAUDREVANGE (TU Munich)
        Material: Slides Video
      • 12:30 Lunch Break 1h30' ( Adriatico Guest House - Cafeteria )
      • 14:00 Topological Data Analysis for Cosmology & the String Landscape 45'
        Speaker: Gary SHIU (University of Wisconsin, Madison)
        Material: Slides Video
      • 14:45 DISCUSSION SESSION 45'
      • 15:30 Coffee Break 30'
      • 16:00 DISCUSSION SESSION 1h0'
      • 19:00 CONFERENCE DINNER 2h0'
  • Wednesday, 12 December 2018
    • 09:00 - 17:00
      • 09:00 Machine Learning Line Bundle Cohomology 45'
        Speaker: Daniel KLAEWER (Max-Planck-Institute)
        Material: Slides Video
      • 09:45 Machine Learning over CICY Threefolds 45'
        Speaker: Challenger MISHRA (ICMAT, Madrid)
        Material: Slides Video
      • 10:30 Coffee Break 30'
      • 11:00 Machine learning for string theory 45'
        Speaker: Harold ERBIN (LMU)
        Material: Slides Video
      • 11:45 Estimating the Number of Calabi-Yau Threefolds in the Kreuzer-Skarke Database 45'
        Speaker: Brent NELSON (Northeastern Univ.)
        Material: Slides Video
      • 12:30 Lunch Break 2h0' ( Adriatico Guest House - Cafeteria )
      • 14:30 Joint ICTP/SISSA String seminar: Classical de Sitter solutions and the swampland 1h0' ( Leonardo Building - Euler Lecture Hall )
        Speaker: David B. ANDRIOT (CERN)
      • 15:30 Coffee Break 30'
      • 16:00 Joint ICTP/SISSA String seminar: On effective descriptions and the stability of de Sitter states 1h0' ( Leonardo Building - Euler Lecture Hall )
        Speaker: Jan Pieter van der SCHAAR (Univ. of Amsterdam)