Frames earthquake magnitude estimation from Sentinel-1 imagery as a metric-learning task that adds pairwise ranking to regression, reporting over 30% MAE improvement versus regression-only baselines.
APACrefauthors \ 2023
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The deep SPAR model shows concurrent floods and droughts becoming more likely in the Upper Danube by 2100 under high emissions, with changes in the dependence between catchments contributing substantially to the increase.
Adding Landsat data to a hybrid ML-physical model for TanDEM-X forest height estimation reduces RMSE by 13.5% and MAE by 16.6% on the Lopé national park site versus the original model.
citing papers explorer
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Estimating Earthquake Magnitude in Sentinel-1 Imagery via Ranking
Frames earthquake magnitude estimation from Sentinel-1 imagery as a metric-learning task that adds pairwise ranking to regression, reporting over 30% MAE improvement versus regression-only baselines.
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Exploring climate change effects on concurrent floods and concurrent droughts via statistical deep learning
The deep SPAR model shows concurrent floods and droughts becoming more likely in the Upper Danube by 2100 under high emissions, with changes in the dependence between catchments contributing substantially to the increase.
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Hybrid Machine Learning Model for Forest Height Estimation from TanDEM-X and Landsat Data
Adding Landsat data to a hybrid ML-physical model for TanDEM-X forest height estimation reduces RMSE by 13.5% and MAE by 16.6% on the Lopé national park site versus the original model.