| The data-driven future of high-energy-density physics PW Hatfield, JA Gaffney, GJ Anderson, S Ali, L Antonelli, ... Nature 593 (7859), 351-361, 2021 | 101* | 2021 |
| Machine learning predictions of a multiresolution climate model ensemble GJ Anderson, DD Lucas Geophysical Research Letters 45 (9), 4273-4280, 2018 | 63 | 2018 |
| Learning to correct climate projection biases B Pan, GJ Anderson, A Goncalves, DD Lucas, CJW Bonfils, J Lee, Y Tian, ... Journal of Advances in Modeling Earth Systems 13 (10), e2021MS002509, 2021 | 46 | 2021 |
| Transfer learning as a tool for reducing simulation bias: application to inertial confinement fusion B Kustowski, JA Gaffney, BK Spears, GJ Anderson, JJ Thiagarajan, ... IEEE Transactions on Plasma Science 48 (1), 46-53, 2019 | 41 | 2019 |
| A review of recent and emerging machine learning applications for climate variability and weather phenomena MJ Molina, TA O’Brien, G Anderson, M Ashfaq, KE Bennett, WD Collins, ... Artificial Intelligence for the Earth Systems 2 (4), 220086, 2023 | 39 | 2023 |
| Improving Seasonal Forecast Using Probabilistic Deep Learning B Pan, GJ Anderson, A Goncalves, DD Lucas, CJW Bonfils, J Lee Journal of Advances in Modeling Earth Systems 14 (3), 20, 2022 | 37 | 2022 |
| Transport equations for the inflationary trispectrum GJ Anderson, DJ Mulryne, D Seery Journal of Cosmology and Astroparticle Physics 2012 (10), 019, 2012 | 32 | 2012 |
| Competing influences of anthropogenic warming, ENSO, and plant physiology on future terrestrial aridity C Bonfils, G Anderson, BD Santer, TJ Phillips, KE Taylor, M Cuntz, ... Journal of Climate 30 (17), 6883-6904, 2017 | 30 | 2017 |
| Designing accurate emulators for scientific processes using calibration-driven deep models JJ Thiagarajan, B Venkatesh, R Anirudh, PT Bremer, J Gaffney, ... Nature Communications 11 (1), 5622, 2020 | 29 | 2020 |
| Suppressing simulation bias in multi-modal data using transfer learning B Kustowski, JA Gaffney, BK Spears, GJ Anderson, R Anirudh, PT Bremer, ... Machine Learning: Science and Technology 3 (1), 015035, 2022 | 16 | 2022 |
| Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations GJ Anderson, JA Gaffney, BK Spears, PT Bremer, R Anirudh, ... arXiv preprint arXiv:2010.13749, 2020 | 15 | 2020 |
| Alpha heating of indirect-drive layered implosions on the National Ignition Facility KL Baker, S MacLaren, O Jones, BK Spears, PK Patel, R Nora, L Divol, ... Physical Review E 107 (1), 015202, 2023 | 11 | 2023 |
| Hydroscaling indirect-drive implosions on the National Ignition Facility KL Baker, O Jones, C Weber, D Clark, PK Patel, CA Thomas, OL Landen, ... Physics of plasmas 29 (6), 2022 | 8 | 2022 |
| Constraining Galileon Inflation D Regan, GJ Anderson, M Hull, D Seery Journal of Cosmology and Astroparticle Physics 2015 (02), 015, 2015 | 6 | 2015 |
| Uncertainty Analysis of Simulations of the Turn‐of‐the‐Century Drought in the Western United States GJ Anderson, DD Lucas, C Bonfils Journal of Geophysical Research: Atmospheres 123 (23), 13,219-13,237, 2018 | 5 | 2018 |
| Optimal bispectrum constraints on single-field models of inflation GJ Anderson, D Regan, D Seery Journal of Cosmology and Astroparticle Physics 2014 (07), 017, 2014 | 4 | 2014 |
| Identifying and correcting climate projection biases using artificial intelligence B Pan, GJ Anderson, DD Lucas, A Goncalves, C Bonfils, J Lee, Y Tian AGU Fall Meeting Abstracts 2020, GC113-0007, 2020 | 3 | 2020 |
| Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data B Kustowski, JA Gaffney, BK Spears, GJ Anderson, R Anirudh, PT Bremer, ... IEEE Transactions on Neural Networks and Learning Systems, 2021 | 2 | 2021 |
| Quantifying uncertainties in predictive models of inertial confinement fusion G Anderson, J Gaffney Bulletin of the American Physical Society 63, 2018 | 2 | 2018 |
| Emulation of seismic-phase traveltimes with machine learning GJ Anderson, SC Myers, N Simmons Geophysical Journal International 235 (3), 2862-2869, 2023 | 1 | 2023 |
celine bonfilsLawrence Livermore National Laboratory在 llnl.gov 的电子邮件经过验证