Format results
-
Learning a phase diagram from dynamics
Evert van Nieuwenburg California Institute of Technology
-
Learning the quantum algorithm for state overlap
Lukasz Cincio Los Alamos National Laboratory
-
The quantum Boltzmann machine
Bert Kappen Radboud Universiteit Nijmegen
-
Simulating quantum annealing via projective quantum Monte Carlo algorithms
Estelle Maeva Inack Perimeter Institute for Theoretical Physics
-
Can we trust phase diagrams produced by artificial neural networks?
Sebastian Wetzel Perimeter Institute for Theoretical Physics
-
Solving physics many-body problems with deep learning
Frank Noe Freie Universität Berlin
-
-
Aspect of Information in Classical and Quantum Neural Networks
Huitao Shen Massachusetts Institute of Technology (MIT) - Department of Physics
-
Reinforcement Learning assisted Quantum Optimization
Matteo Wauters SISSA Scuola Internazionale Superiore di Studi Avanzati
-
Phase Detection with Neural Networks: Interpreting the Black Box
Anna Dawid-Łękowska University of Warsaw
-
Physical footprints of intrinsic sign problems
Zohar Ringel Hebrew University of Jerusalem
-
Controlling Majorana zero modes with machine learning
Luuk Coopmans Dublin Institute for Advanced Studies