most citedCapabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM

63 citations · 64 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 1 cited

Extension of Convolutional Neural Network along Temporal and Vertical Directions for Precipitation Downscaling

Takeyoshi Nagasato, Kei Ishida, Ali Ercan +4

Deep learning has been utilized for the statistical downscaling of climate data. Specifically, a two-dimensional (2D) convolutional neural network (CNN) has been successfully appli…

physics.ao-ph2021★ 63 cited

Capabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM

Kazuki Yokoo, Kei Ishida, Ali Ercan +4

This study investigates the relationships which deep learning methods can identify between the input and output data. As a case study, rainfall-runoff modeling in a snow-dominated…