DSPR decouples temporal patterns and residual dynamics with physics priors to improve accuracy and plausibility in non-stationary industrial forecasting.
MSGNet[ 4]: Leverages frequency- domain graph convolutions for multi-scale inter-series correlations
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DSPR: Dual-Stream Physics-Residual Networks for Trustworthy Industrial Time Series Forecasting
DSPR decouples temporal patterns and residual dynamics with physics priors to improve accuracy and plausibility in non-stationary industrial forecasting.