Hydrology Paper of the Day @christost.bsky.social @georgiapapachar.bsky.social on consistent loss functions: explicit definitions and examples; how these loss functions are utilized to evaluate point predictions; loss functions and transformations; and applications to climatology and hydrology.

Happy (😊) to share our latest paper on variable transformations in consistent loss functions:
👉 doi.org/10.1016/j.kn...
👉 authors.elsevier.com/c/1mSkA3OAb9...
#LossFunction #MachineLearning #Prediction
@christost.bsky.social

Applying transforms within loss functions motivated our new paper with @georgiapapachar.bsky.social.
Free access: authors.elsevier.com/a/1mSkA3OAb9...
Available here: doi.org/10.1016/j.kn...

Hydrology Paper of the Day @georgiapapachar.bsky.social on estimating uncertainties associated with gridded precipitation data products derived from satellite remote sensing: non-linear ensemble learning and quantile loss functions; predictor variable reduction; stacking; and assessing performance.

Very happy (😊) to share our new paper, in which we introduce deep Huber quantile regression networks:
👉 doi.org/10.1016/j.ne...
👉 authors.elsevier.com/a/1knnz3BBjK...
#DeepLearning #MachineLearning #PredictiveUncertainty