| ClimateBench v1. 0: A benchmark for data‐driven climate projections D Watson‐Parris, Y Rao, D Olivié, Ø Seland, P Nowack, G Camps‐Valls, ... Journal of Advances in Modeling Earth Systems 14 (10), e2021MS002954, 2022 | 34 | 2022 |
| Deconditional Downscaling with Gaussian processes SL Chau, S Bouabid, D Sejdinovic Advances in Neural Information Processing Systems 34, 17813-17825, 2021 | 15 | 2021 |
| NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations P Harder, W Jones, R Lguensat, S Bouabid, J Fulton, D Quesada-Chacón, ... NeurIPS Workshop on Tackling Climate Change with Machine Learning, 2020, 2020 | 7 | 2020 |
| Mixup regularization for region proposal based object detectors S Bouabid, V Delaitre arXiv preprint arXiv:2003.02065, 2020 | 5 | 2020 |
| Predicting landsat reflectance with deep generative fusion S Bouabid, M Chernetskiy, M Rischard, J Gamper NeurIPS Workshop on Tackling Climate Change with Machine Learning, 2020, 2020 | 3 | 2020 |
| ClimateBench: A benchmark dataset for data-driven climate projections D Watson-Parris, Y Rao, D Olivié, Ø Seland, PJ Nowack, G Camps-Valls, ... Authorea Preprints, 2022 | 2 | 2022 |
| Reconstructing Aerosols Vertical Profiles with Aggregate Output Learning S Stefanovic, S Bouabid, P Stier, A Nenes, D Sejdinovic ICML Workshop on Tackling Climate Change with Machine Learning, 2021, 2021 | 1 | 2021 |
| Domain Generalisation via Imprecise Learning A Singh, SL Chau, S Bouabid, K Muandet arXiv preprint arXiv:2404.04669, 2024 | | 2024 |
| Analyzing Climate Scenarios Using Dynamic Mode Decomposition With Control N Mankovich, S Bouabid, G Camps-Valls EGU24, 2024 | | 2024 |
| FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation S Bouabid, D Sejdinovic, D Watson-Parris arXiv preprint arXiv:2307.10052, 2023 | | 2023 |
| Probabilistic climate emulation with physics-constrained Gaussian processes S Bouabid, D Sejdinovic, D Watson-Parris EGU General Assembly Conference Abstracts, EGU-15660, 2023 | | 2023 |
| Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge S Bouabid, J Fawkes, D Sejdinovic International Conference on Machine Learning 202, 2885--2913, 2023 | | 2023 |
| AODisaggregation: toward global aerosol vertical profiles S Bouabid, D Watson-Parris, S Stefanović, A Nenes, D Sejdinovic arXiv preprint arXiv:2205.04296, 2022 | | 2022 |
| Bayesian inference for aerosol vertical profiles S Bouabid, D Watson-Parris, D Sejdinovic NeurIPS Workshop on Tackling Climate Change with Machine Learning, 2022, 2022 | | 2022 |
