| Reducing autocorrelation times in lattice simulations with generative adversarial networks JM Pawlowski, JM Urban Machine Learning: Science and Technology 1 (4), 045011, 2020 | 62 | 2020 |
| Spectral reconstruction with deep neural networks L Kades, JM Pawlowski, A Rothkopf, M Scherzer, JM Urban, SJ Wetzel, ... Physical Review D 102 (9), 096001, 2020 | 55 | 2020 |
| Reconstructing QCD spectral functions with Gaussian processes J Horak, JM Pawlowski, J Rodríguez-Quintero, J Turnwald, JM Urban, ... Physical Review D 105 (3), 036014, 2022 | 54 | 2022 |
| Flow-based sampling for fermionic lattice field theories MS Albergo, G Kanwar, S Racaniere, DJ Rezende, JM Urban, D Boyda, ... Physical Review D 104 (11), 114507, 2021 | 49 | 2021 |
| Towards novel insights in lattice field theory with explainable machine learning S Blücher, L Kades, JM Pawlowski, N Strodthoff, JM Urban Physical Review D 101 (9), 094507, 2020 | 48 | 2020 |
| 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 | 28 | 2022 |
| 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 | 27 | 2022 |
| Sampling QCD field configurations with gauge-equivariant flow models R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ... Sissa Medialab, 2022 | 18 | 2022 |
| Aspects of scaling and scalability for flow-based sampling of lattice QCD R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ... The European Physical Journal A 59 (11), 257, 2023 | 10 | 2023 |
| 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 | 9 | 2023 |
| Nonperturbative strong coupling at timelike momenta J Horak, JM Pawlowski, J Turnwald, JM Urban, N Wink, S Zafeiropoulos Physical Review D 107 (7), 076019, 2023 | 9 | 2023 |
| Confinement in non-Abelian lattice gauge theory via persistent homology D Spitz, JM Urban, JM Pawlowski Physical Review D 107 (3), 034506, 2023 | 8 | 2023 |
| Flow-based density of states for complex actions JM Pawlowski, JM Urban Physical Review D 108 (5), 054511, 2023 | 7 | 2023 |
| Flow-based density of states for complex actions (2022) JM Pawlowski, JM Urban arXiv preprint arXiv:2203.01243, 0 | 6 | |
| Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions, 2022 R Abbott, MS Albergo, D Boyda, K Cranmer, DC Hackett, G Kanwar, ... URL https://arxiv. org/abs/2207.08945, 0 | 6 | |
| Yang-Mills glueball masses from spectral reconstruction JM Pawlowski, CS Schneider, J Turnwald, JM Urban, N Wink Physical Review D 108 (7), 076018, 2023 | 5 | 2023 |
| Flow-based sampling in the lattice schwinger model at criticality, 2022 MS Albergo, D Boyda, K Cranmer, DC Hackett, G Kanwar, S Racanière, ... URL https://arxiv. org/abs/2202.11712, 0 | 5 | |
| Practical applications of machine-learned flows on gauge fields R Abbott, MS Albergo, D Boyda, DC Hackett, G Kanwar, F Romero-López, ... arXiv preprint arXiv:2404.11674, 2024 | | 2024 |
| Multiscale Normalizing Flows for Gauge Theories R Abbott, MS Albergo, D Boyda, DC Hackett, G Kanwar, F Romero-López, ... arXiv preprint arXiv:2404.10819, 2024 | | 2024 |
| Applications of flow models to the generation of correlated lattice QCD ensembles R Abbott, A Botev, D Boyda, DC Hackett, G Kanwar, S Racanière, ... arXiv preprint arXiv:2401.10874, 2024 | | 2024 |
Jan M. PawlowskiUniversität HeidelbergVerified email at thphys.uni-heidelberg.de
