| Flow-based generative models for Markov chain Monte Carlo in lattice field theory MS Albergo, G Kanwar, PE Shanahan Physical Review D 100 (3), 034515, 2019 | 257 | 2019 |
| Equivariant flow-based sampling for lattice gauge theory G Kanwar, MS Albergo, D Boyda, K Cranmer, DC Hackett, S Racaniere, ... Physical Review Letters 125 (12), 121601, 2020 | 232 | 2020 |
| Sampling using gauge equivariant flows D Boyda, G Kanwar, S Racanière, DJ Rezende, MS Albergo, K Cranmer, ... Physical Review D 103 (7), 074504, 2021 | 161 | 2021 |
| Normalizing flows on tori and spheres DJ Rezende, G Papamakarios, S Racaniere, M Albergo, G Kanwar, ... International Conference on Machine Learning, 8083-8092, 2020 | 161 | 2020 |
| Simit: A language for physical simulation F Kjolstad, S Kamil, J Ragan-Kelley, DIW Levin, S Sueda, D Chen, ... ACM Transactions on Graphics (TOG) 35 (2), 1-21, 2016 | 75 | 2016 |
| Flow-based sampling for fermionic lattice field theories MS Albergo, G Kanwar, S Racanière, DJ Rezende, JM Urban, D Boyda, ... Physical Review D 104 (11), 114507, 2021 | 58 | 2021 |
| Introduction to normalizing flows for lattice field theory MS Albergo, D Boyda, DC Hackett, G Kanwar, K Cranmer, S Racanière, ... arXiv preprint arXiv:2101.08176, 2021 | 48 | 2021 |
| Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions R Abbott, MS Albergo, D Boyda, K Cranmer, DC Hackett, G Kanwar, ... Physical Review D 106 (7), 074506, 2022 | 40 | 2022 |
| Flow-based sampling for multimodal distributions in lattice field theory DC Hackett, CC Hsieh, MS Albergo, D Boyda, JW Chen, KF Chen, ... arXiv preprint arXiv:2107.00734, 2021 | 40 | 2021 |
| Path integral contour deformations for observables in gauge theory W Detmold, G Kanwar, H Lamm, ML Wagman, NC Warrington Physical Review D 103 (9), 094517, 2021 | 39 | 2021 |
| Path integral contour deformations for noisy observables W Detmold, G Kanwar, ML Wagman, NC Warrington Physical Review D 102 (1), 014514, 2020 | 31 | 2020 |
| Flow-based sampling in the lattice Schwinger model at criticality MS Albergo, D Boyda, K Cranmer, DC Hackett, G Kanwar, S Racanière, ... Physical Review D 106 (1), 014514, 2022 | 30 | 2022 |
| Applications of flow models to the generation of correlated lattice QCD ensembles R Abbott, A Botev, D Boyda, DC Hackett, G Kanwar, S Racanière, ... Physical Review D 109 (9), 094514, 2024 | 29 | 2024 |
| Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics K Cranmer, G Kanwar, S Racanière, DJ Rezende, PE Shanahan Nature Reviews Physics, 1-10, 2023 | 26 | 2023 |
| Sampling QCD field configurations with gauge-equivariant flow models R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ... arXiv preprint arXiv:2208.03832, 2022 | 20 | 2022 |
| Normalizing flows for lattice gauge theory in arbitrary space-time dimension R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ... arXiv preprint arXiv:2305.02402, 2023 | 18 | 2023 |
| Real-time lattice gauge theory actions: Unitarity, convergence, and path integral contour deformations G Kanwar, ML Wagman Physical Review D 104 (1), 014513, 2021 | 18 | 2021 |
| Phase unwrapping and one-dimensional sign problems W Detmold, G Kanwar, ML Wagman Physical Review D 98 (7), 074511, 2018 | 18 | 2018 |
| transition form factor and the hadronic light-by-light -pole contribution to the muon from lattice QCD C Alexandrou, S Bacchio, S Burri, J Finkenrath, A Gasbarro, ... Physical Review D 108 (5), 054509, 2023 | 11 | 2023 |
| Machine learning and variational algorithms for lattice field theory G Kanwar Massachusetts Institute of Technology, 2021 | 11 | 2021 |
Phiala ShanahanMassachusetts Institute of Technology在 mit.edu 的电子邮件经过验证