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
    • Predicted Chl_a of STIMP and Climate mean
STIMP
  • Supplementary main results
  • View page source

Supplementary main results

Code for reproducing the main results presented in the supplementary

  • Imputation length (including half year and one-and-a-half years)
    • Half-year Imputation
    • One-and-a-half-years Imputation
  • Prediction Length
    • Different Prediction Horizons in PRE
    • Different Prediction Horizons in Chesapeake Bay
    • Different Prediction Horizons in Gulf of the Mexico
    • Different Prediction Horizons in Yangtze River Estuary
  • Recurrent Prediction
    • Recurrent Prediction
  • Case study: predicted Chl_a of STIMP and baselines trained on imputed dataset
    • Predicted Chl_a of STIMP and baselines trained on imputed dataset at three locations
  • STIMP, MaskedAE and Lin-itp
    • 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
    • Overall improvement of STIMP compared to two climate mean predictions
    • Predicted Chl_a of STIMP and two climate mean state at four locations
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