| Exascale deep learning for climate analytics T Kurth, S Treichler, J Romero, M Mudigonda, N Luehr, E Phillips, ... SC18: International Conference for High Performance Computing, Networking …, 2018 | 313 | 2018 |
| ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather K Kashinath, M Mudigonda, S Kim, L Kapp-Schwoerer, A Graubner, ... Geoscientific Model Development 14 (1), 107-124, 2021 | 58* | 2021 |
| Segmenting and tracking extreme climate events using neural networks M Mudigonda, S Kim, A Mahesh, S Kahou, K Kashinath, D Williams, ... Deep Learning for Physical Sciences (DLPS) Workshop, held with NIPS Conference, 2017 | 39 | 2017 |
| Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1. 0.1 TA O'Brien, MD Risser, B Loring, AA Elbashandy, H Krishnan, J Johnson, ... Geoscientific Model Development 13 (12), 6131-6148, 2020 | 23 | 2020 |
| Forecasting El Niño with convolutional and recurrent neural networks A Mahesh, M Evans, G Jain, M Castillo, A Lima, B Lunghino, H Gupta, ... 33rd Conference on Neural Information Processing Systems (NeurIPS 2019 …, 2019 | 22 | 2019 |
| Identifying Atmospheric Rivers and their Poleward Latent Heat Transport with Generalizable Neural Networks: ARCNNv1 A Mahesh, T O'Brien, B Loring, A Elbashandy, W Boos, W Collins EGUsphere 2023, 1-36, 2023 | 8* | 2023 |
| Deep Learning for Detecting Extreme Weather Patterns M Mudigonda, P Ram, K Kashinath, E Racah, A Mahesh, Y Liu, ... Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote …, 2021 | 7* | 2021 |
| A Practical Probabilistic Benchmark for AI Weather Models ND Brenowitz, Y Cohen, J Pathak, A Mahesh, B Bonev, T Kurth, ... arXiv preprint arXiv:2401.15305, 2024 | 2 | 2024 |
| Exascale Deep Learning for Climate Science M Prabhat, T Kurth, S Treichler, J Romero, M Mudigonda, A Mahesh, ... 99th American Meteorological Society Annual Meeting, 2019 | 1 | 2019 |
| Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction JD Willard, P Harrington, S Subramanian, A Mahesh, TA O'Brien, ... arXiv preprint arXiv:2404.19630, 2024 | | 2024 |
| The Graduate Climate Conference: Insights on a Community-Driven Student Conference and its Merits for Early-Career Researchers S Wang, M Galochkina, A Liu, A Mahesh, R Moskvichev, C Nsude, ... AGU23, 2023 | | 2023 |
| Machine learning to generate gridded extreme precipitation data sets for global land areas with limited in situ measurements M Risser, A Rhoades, A Mahesh Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States); Univ …, 2021 | | 2021 |
| Tutorial on Machine Learning and Deep Learning for the Environmental and Geosciences K Kashinath, I Ebert-Uphoff, DJ Gagne, K Dagon, P Gentine, ... AGU Fall Meeting 2020, 2020 | | 2020 |
| SeasonalBench: A statistical seasonal forecasting benchmark M cody Evans, A Mahesh, A Ahmadalipour, S c Rasp, E Rojas AGU Fall Meeting 2020, 2020 | | 2020 |
| Crop Stage Estimation: A Multi-Satellite Historical Model and a Scalable Neural Network Forecaster N Padmanabhan, A Mahesh, A Sripathy, A Sujithkumar, A Sun, C Snell, ... AGU Fall Meeting Abstracts 2020, IN011-08, 2020 | | 2020 |
| SeasonalBench: A statistical seasonal forecasting benchmark MC Evans, A Mahesh, A Ahmadalipour, SC Rasp, E Rojas AGU Fall Meeting Abstracts 2020, IN011-01, 2020 | | 2020 |
| Building a Platform to Communicate Long-Term Climate Projections and Climate Analogs C Cross, A Mahesh, MC Evans, H Gupta AGU Fall Meeting Abstracts 2020, GC108-02, 2020 | | 2020 |
| Probabilistic Detection of Atmospheric Rivers Across Climate Datasets and Resolutions with Neural Networks A Mahesh, TA O'Brien, A Elbashandy, B Guan, K Kashinath, LR Leung, ... AGU Fall Meeting Abstracts 2020, A199-02, 2020 | | 2020 |
| Using Deep Learning to Detect Atmospheric Rivers across Climate Datasets and Resolutions A Mahesh, TA O'Brien, K Kashinath, M Mudigonda, M Prabhat, ... 100th American Meteorological Society Annual Meeting, 2020 | | 2020 |
| Forcasting el Nino with Convolutional Recurrent Networks M cody Evans, G Jain, A Mahesh, CFG Ospina, M Castillo, B Lunghino, ... AGU Fall Meeting 2019, 2019 | | 2019 |
