Roger Melko
(University of Waterloo, Canada)
Titus Neupert
(University of Zurich, Switzerland)
Simon Trebst
(University of Cologne, Germany)
The workshop covers the emerging research area that applies machine learning techniques to analyze, represent, and solve quantum many-body systems in condensed matter physics. This includes problems of phase classification and characterization, state compression, feature extraction, wavefunction representation using neural networks, and connections between tensor networks and machine learning.
Erez Berg (US)
Giuseppe Carleo (CH)
Juan Carrasquilla (CA)
Ignacio Cirac (DE)
Dong-Ling Deng (US)
Claudia Draxl (DE)
Jens Eisert (DE)
Luca Ghiringhelli (DE)
David Gross (DE)
Masatoshi Imada (JP)
Eun-Ah Kim (US)
Maciej Koch-Janusz (CH)
Nicolas Regnault (FR)
Matthias Rupp (DE)
Miles Stoudenmire (US)
Giacomo Torlai (CA)
Jordi Tura i Brugués (DE)
Evert van Nieuwenburg (US)
Frank Verstraete (BE)
Lei Wang (CN)
Yi Zhang (US)