| Safe reinforcement learning with model uncertainty estimates B Lütjens, M Everett, JP How 2019 International Conference on Robotics and Automation (ICRA), 8662-8668, 2019 | 233 | 2019 |
| Certified adversarial robustness for deep reinforcement learning B Lütjens, M Everett, JP How Conference on Robot Learning (CoRL), 1328-1337, 2020 | 105 | 2020 |
| GEO-Bench: Toward Foundation Models for Earth Monitoring A Lacoste, N Lehmann, P Rodriguez, ED Sherwin, H Kerner, B Lütjens, ... NeurIPS Datasets and Benchmarks, 2023 | 80* | 2023 |
| Certifiable robustness to adversarial state uncertainty in deep reinforcement learning M Everett, B Lütjens, JP How IEEE Transactions on Neural Networks and Learning Systems 33 (9), 4184-4198, 2021 | 68* | 2021 |
| The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks SR Cachay, E Erickson, AFC Bucker, E Pokropek, W Potosnak, S Bire, ... arXiv preprint arXiv:2104.05089, 2021 | 52* | 2021 |
| ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation S Yu, W Hannah, L Peng, J Lin, MA Bhouri, R Gupta, B Lütjens, JC Will, ... Advances in Neural Information Processing Systems 36, 22070-22084, 2023 | 41* | 2023 |
| ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery G Reiersen, D Dao, B Lütjens, K Klemmer, K Amara, A Steinegger, ... AAAI-22, 2022 | 41* | 2022 |
| Digital Twin Earth--Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators P Jiang, N Meinert, H Jordão, C Weisser, S Holgate, A Lavin, B Lütjens, ... 2021 NeurIPS Workshop on Machine Learning for the Physical Sciences (ML4PS), 2021 | 40 | 2021 |
| Generating Physically-Consistent Satellite Imagery for Climate Visualizations B Lütjens, B Leshchinskiy, O Boulais, F Chishtie, N Díaz-Rodríguez, ... IEEE Transactions on Geoscience and Remote Sensing, 2024 | 39* | 2024 |
| Spectral PINNs: Fast uncertainty propagation with physics-informed neural networks B Lütjens, CH Crawford, M Veillette, D Newman 2021 NeurIPS Workshop on the Symbiosis of Deep Learning and Differential, 2021 | 26* | 2021 |
| Machine learning-based estimation of forest carbon stocks to increase transparency of forest preservation efforts B Lütjens, L Liebenwein, K Kramer 2019 NeurIPS Workshop on Tackling Climate Change with AI (CCAI), 2019 | 20 | 2019 |
| WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data R Kurinchi-Vendhan, B Lütjens, R Gupta, L Werner, D Newman 2021 NeurIPS Workshop on Tackling Climate Change with Machine Learning (CCML), 2021 | 19 | 2021 |
| Multiscale neural operator: Learning fast and grid-independent pde solvers B Lütjens, CH Crawford, CD Watson, C Hill, D Newman arXiv preprint arXiv:2207.11417, 2022 | 15 | 2022 |
| Ocean emulation with Fourier neural operators: Double gyre S Bire, B Lütjens, K Azizzadenesheli, A Anandkumar, CN Hill Authorea Preprints, 2023 | 10* | 2023 |
| Teaching computer vision for ecology E Cole, S Stathatos, B Lütjens, T Sharma, J Kay, J Parham, ... arXiv preprint arXiv:2301.02211, 2023 | 7 | 2023 |
| TrueBranch: Metric Learning-based Verification of Forest Conservation Projects S Santamaria*, D Dao*, B Lütjens*, C Zhang Best Proposal Paper at 2020 ICLR CCML, 2020 | 6 | 2020 |
| Climsim-online: A large multi-scale dataset and framework for hybrid ml-physics climate emulation S Yu, Z Hu, A Subramaniam, W Hannah, L Peng, J Lin, MA Bhouri, ... arXiv preprint arXiv:2306.08754, 2023 | 4 | 2023 |
| The impact of internal variability on benchmarking deep learning climate emulators B Lütjens, R Ferrari, D Watson-Parris, N Selin arXiv preprint arXiv:2408.05288, 2024 | 1 | 2024 |
| Dailymelt: Diffusion-based models for spatiotemporal downscaling of (ant-) arctic surface meltwater maps B Lütjens, P Alexander, R Antwerpen, G Cervone, M Kearney, B Luo, ... EGU General Assembly, 2023 | 1 | 2023 |
| Deep Learning Emulators for Accessible Climate Projections B Lütjens PhD Thesis, Massachusetts Institute of Technology, 2023 | 1 | 2023 |
Dava NewmanDirector, MIT Media Lab; Apollo Professor of Astronautics, MITmit.edu üzerinde doğrulanmış e-posta adresine sahip