| The boundary for quantum advantage in Gaussian boson sampling JFF Bulmer, BA Bell, RS Chadwick, AE Jones, D Moise, A Rigazzi, ... Science advances 8 (4), eabl9236, 2022 | 91 | 2022 |
| Using machine learning at scale in numerical simulations with SmartSim: An application to ocean climate modeling S Partee, M Ellis, A Rigazzi, AE Shao, S Bachman, G Marques, B Robbins Journal of Computational Science 62, 101707, 2022 | 76 | 2022 |
| Time-dependent visualization of Lagrangian coherent structures by grid advection F Sadlo, A Rigazzi, R Peikert Topological Methods in Data Analysis and Visualization: Theory, Algorithms …, 2011 | 68 | 2011 |
| Recombination of artificial neural networks A Vose, J Balma, A Heye, A Rigazzi, C Siegel, D Moise, B Robbins, ... arXiv preprint arXiv:1901.03900, 2019 | 6 | 2019 |
| A parallel multigrid method for constrained minimization problems and its application to friction, contact, and obstacle problems R Krause, A Rigazzi, J Steiner Computing and Visualization in Science 18, 1-15, 2016 | 6 | 2016 |
| In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD R Balin, F Simini, C Simpson, A Shao, A Rigazzi, M Ellis, S Becker, ... arXiv preprint arXiv:2306.12900, 2023 | 5 | 2023 |
| The effects of roughness on the area of contact and on the elastostatic friction AP Rigazzi | 5 | 2014 |
| Combining machine learning with computational fluid dynamics using OpenFOAM and SmartSim T Maric, ME Fadeli, A Rigazzi, A Shao, A Weiner Meccanica, 1-20, 2024 | 4 | 2024 |
| DC-S3GD: Delay-Compensated Stale-Synchronous SGD for Large-Scale Decentralized Neural Network Training A Rigazzi 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), 62-68, 2019 | 3 | 2019 |
| 19th OpenFOAM Workshop-Combining Machine Learning with Computational Fluid Dynamics using OpenFOAM and SmartSim T Maric, AE Shao, A Rigazzi, M Ellis, EM Fadeli, K Yuan, A Weiner | | 2024 |
| Efficiently combining Machine Learning with OpenFOAM using SmartSim-Slides T Maric, A Shao, A Rigazzi, M Ellis, M Fadeli, A Weiner | | 2023 |
| Advection of sampling grids for efficient computation of trajectory-based quantities A Rigazzi ETH, Eidgenössische Technische Hochschule Zürich, Institut für Computational …, 2008 | | 2008 |
| Using Machine Learning at Scale in HPC Simulations with SmartSim S Partee, M Ellis, A Rigazzi, S Bachman, G Marques, A Shao, B Robbins | | |
| Yin, Junqi 84 Zhang, Zhao 45, 69 C Adams, AA Awan, D Barajas-Solano, JK Bassett, D Bhowmik, T Bicer, ... | | |
