Machine learning effective models for quantum systems JB Rigo, AK Mitchell Physical Review B 101 (24), 241105, 2020 | 22 | 2020 |
Automatic differentiable numerical renormalization group JB Rigo, AK Mitchell Physical Review Research 4 (1), 013227, 2022 | 15 | 2022 |
Linear response quantum transport through interacting multi-orbital nanostructures EL Minarelli, JB Rigo, AK Mitchell arXiv preprint arXiv:2209.01208, 2022 | 11 | 2022 |
Times of maximum of CY Aquarii: the 2010 season C Sterken, C Wiedemair, T Tuvikene, J Rigo, T Munaro, M Untergassmair The Journal of Astronomical Data, Vol. 17, 2 17, 2011 | 4 | 2011 |
Multiband photometry of CY Aquarii: the 2011 season C Sterken, C Wiedemair, T Munaro, J Rigo, J Durnwalder, A Kirchler, ... The Journal of Astronomical Data, Vol. 18, 2 18, 2012 | 3 | 2012 |
Two-channel charge-Kondo physics in graphene quantum dots EL Minarelli, JB Rigo, AK Mitchell Nanomaterials 12 (9), 1513, 2022 | 2 | 2022 |
Unsupervised Model Learning for Quantum Impurity Systems JB Rigo, AK Mitchell arXiv preprint arXiv:2401.13600, 2024 | 1 | 2024 |
VizieR Online Data Catalog: CY Aqr multiband photometry: 2011 season (Sterken+, 2012) C Sterken, C Wiedemair, T Munaro, J Rigo, J Durnwalder, A Kirchler, ... VizieR Online Data Catalog (other) 350, J/other/JAD/18, 2012 | 1 | 2012 |
Unsupervised learning of effective quantum impurity models JB Rigo, AK Mitchell Physical Review Research 6 (4), 043044, 2024 | | 2024 |
Is the ground state of Anderson's impurity model a recurrent neural network? J Rigo, M Schmitt Bulletin of the American Physical Society, 2024 | | 2024 |
Automated derivation of effective models for quantum impurity models J Rigo, A Mitchell APS March Meeting Abstracts 2022, T47. 010, 2022 | | 2022 |
Generative Model Learning for molecular electronics A Mitchell, J Rigo, S Sen Bulletin of the American Physical Society 66, 2021 | | 2021 |
Machine learning effective models from a Boltzmann perspective J Rigo, A Mitchell Bulletin of the American Physical Society 65, 2020 | | 2020 |
Machine learning effective models for quantum systems A Mitchell, J Rigo Bulletin of the American Physical Society 65, 2020 | | 2020 |
Artifcial neural networks as function approximators in quantum many-body physics J Rigo Universität Innsbruck, 2018 | | 2018 |
VizieR Online Data Catalog: CY Aqr differential light curves (Sterken+, 2011) C Sterken, C Wiedemair, T Tuvikene, J Rigo, T Munaro, M Untergassmair, ... VizieR Online Data Catalog (other) 350, J/other/JAD/17, 2011 | | 2011 |