147 citations · 259 across the 4 of their papers we have counts for
4 papers
High-accuracy variational Monte Carlo for frustrated magnets with deep neural networks
Christopher Roth, Attila Szabó, Allan MacDonald
We show that neural quantum states based on very deep (4--16-layered) neural networks can outperform state-of-the-art variational approaches on highly frustrated quantum magnets, i…
NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems
Filippo Vicentini, Damian Hofmann, Attila Szabó +8
We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum physics. NetKet is built around neural-network quantum states and provides efficient algorithms…
Group Convolutional Neural Networks Improve Quantum State Accuracy
Christopher Roth, Allan H. MacDonald
Neural networks are a promising tool for simulating quantum many body systems. Recently, it has been shown that neural network-based models describe quantum many body systems more…
Iterative Retraining of Quantum Spin Models Using Recurrent Neural Networks
Christopher Roth
Modeling quantum many-body systems is enormously challenging due to the exponential scaling of Hilbert dimension with system size. Finding efficient compressions of the wavefunctio…