NetKet 3: Machine learning toolbox for many-body quantum systems F Vicentini, D Hofmann, A Szabó, D Wu, C Roth, C Giuliani, G Pescia, ...
SciPost Physics Codebases, 007, 2022
75 2022 Group convolutional neural networks improve quantum state accuracy C Roth, AH MacDonald
arXiv preprint arXiv:2104.05085, 2021
36 2021 Iterative retraining of quantum spin models using recurrent neural networks C Roth
arXiv preprint arXiv:2003.06228, 2020
33 2020 Kernel rnn learning (kernl) C Roth, I Kanitscheider, I Fiete
International Conference on Learning Representations, 2018
23 2018 High-accuracy variational Monte Carlo for frustrated magnets with deep neural networks C Roth, A Szabó, AH MacDonald
Physical Review B 108 (5), 054410, 2023
22 2023 Spin Frustration and a `Half Fire, Half Ice' Critical Point from Nonuniform -Factors WG Yin, CR Roth, AM Tsvelik
arXiv preprint arXiv:1510.00030, 2015
4 2015 Spin frustration and an exotic critical point in ferromagnets from nonuniform opposite factors W Yin, CR Roth, AM Tsvelik
Physical Review B 109 (5), 054427, 2024
2 2024 Codebase release 3.4 for NetKet F Vicentini, D Hofmann, A Szabó, D Wu, C Roth, C Giuliani, G Pescia, ...
SciPost Physics Codebases, 007, 2022
1 2022 Investigating frustrated magnetism with symmetry-aware neural networks CR Roth
2023 Learning the Ground State Wavefunction of Periodic Systems Using Recurrent Neural Networks C Roth, A MacDonald
Bulletin of the American Physical Society 65, 2020
2020