STIMP
0.1.0
Installation
Usage
Train baselines
Four representative coastal ocean area analysis
Supplementary main results
Imputation length (including half year and one-and-a-half years)
Prediction Length
Recurrent Prediction
Case study: predicted Chl_a of STIMP and baselines trained on imputed dataset
STIMP, MaskedAE and Lin-itp
Imputation of DINEOF with different t
STIMP vs DINEOF with different values of t
Predicted Chl_a of STIMP and Climate mean
STIMP
Supplementary main results
Imputation of DINEOF with different t
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Imputation of DINEOF with different t
STIMP vs DINEOF with different values of t
missing rate is equal to 0.1
missing rate is equal to 0.3
missing rate is equal to 0.5
missing rate is equal to 0.7
missing rate is equal to 0.9