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Models/MIM*

MIM*

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision3 results

  • VideoonMoving MNIST
    MAE· 2018-11-19
    101.1
    best: 41.96 (PredFormer)
    SOTA
    Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsarXiv:1811.07490
  • VideoonMoving MNIST
    MSE· 2018-11-19
    44.2
    best: 11.62 (PredFormer)
    SOTA
    Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsarXiv:1811.07490
  • VideoonMoving MNIST
    SSIM· 2018-11-19
    0.91
    best: 0.975 (MSPred)
    SOTA
    Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsarXiv:1811.07490

Time Series3 results

  • Video PredictiononMoving MNIST
    MAE· 2018-11-19
    101.1
    best: 41.96 (PredFormer)
    SOTA
    Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsarXiv:1811.07490
  • Video PredictiononMoving MNIST
    MSE· 2018-11-19
    44.2
    best: 11.62 (PredFormer)
    SOTA
    Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsarXiv:1811.07490
  • Video PredictiononMoving MNIST
    SSIM· 2018-11-19
    0.91
    best: 0.975 (MSPred)
    SOTA
    Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsarXiv:1811.07490