Sensorformer uses a two-stage cross-patch attention mechanism with global-patch compression to improve multivariate time series forecasting accuracy while reducing attention complexity.
Are transformers effective for time series forecasting?
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Sensorformer: Cross-patch attention with global-patch compression is effective for high-dimensional multivariate time series forecasting
Sensorformer uses a two-stage cross-patch attention mechanism with global-patch compression to improve multivariate time series forecasting accuracy while reducing attention complexity.