Knowledge Distillation for Improving Deep Learning‐Based Hydrological Prediction and Fine‐Tuning
Abstract This paper introduces knowledge distillation (KD) as a method for improving deep learning (DL)‐based hydrological prediction. The performance of DL models, including long short‐term memory networks (LSTMs), is highly dependent on model structure and training data quality, posing challenges...
I tiakina i:
| Ngā kaituhi matua: | , , , |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Wiley
2026-06-01
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| Rangatū: | Journal of Geophysical Research: Machine Learning and Computation |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1029/2025JH001081 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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