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SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction

NeurIPS 2022 · Time series › Long-term forecasting · approach: Spatiotemporal forecasting models · 246 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use SCINet's downsample-convolve-interact architecture instead of the strongest listed baselineSCINet · Short-term forecasting, Solar-Energy, Traffic, Electricity, and Exchange-Rate, horizon 3RSE: Solar-Energy: 0.1803 -> 0.1775; Traffic: 0.4487 -> 0.4216; Electricity: 0.0823 -> 0.0740; Exchange-Rate: 0.0174 -> 0.017Helped
Use SCINet instead of AutoformerSCINet · Exchange-Rate, long-term forecasting, horizon 96MSE: 0.197 -> 0.061Helped
Use SCINet instead of AutoformerSCINet · ETTh1 multivariate, horizon 24MSE: 0.406 -> 0.300Helped
Remove interactive learning between the two downsampled subsequences (ablation)SCINet SCI-Block · ETTh1 and PEMS08, multiple prediction horizonsprediction accuracyHurt
Share the convolution weights across the SCI-Block modules (ablation)SCINet SCI-Block · ETTh1 and PEMS08, multiple prediction horizonsprediction accuracyHurt
Remove the residual connection (ablation)SCINet · ETTh1 and PEMS08prediction accuracyHurt
Remove the fully connected decoder (ablation)SCINet · ETTh1 and PEMS08prediction accuracyHurt
Increase the number of levels from 3 to 4 (ablation)SCINet · ETTh1, horizon 24, look-back 192MSE: 0.330 -> 0.325Helped
Increase the number of stacks from 1 to 3 (ablation)SCINet · ETTh1, horizon 24, look-back 24MSE: 0.405 -> 0.374Helped
Increase the number of stacks from 1 to 3 (ablation)SCINet · ETTh1, horizon 24, look-back 192MSE: 0.330 -> 0.363Hurt
Vary addition/subtraction choices in the interaction update (ablation)SCINet SCI-Block · PEMS03, PEMS04, PEMS07, and PEMS08MAE: PEMS03: 15.06–15.30; PEMS04: 19.21–19.32; PEMS07: 21.63–21.77; PEMS08: 15.72–15.84No clear effect

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