In a forecasting problem, we have $\mathcal P$, the priors, e.g., price and demand is negatively …

The temporal convolution is responsible for capturing temporal patterns in a sequence.

Mix-hop is a strategy to avoid oversmoothing in GNN

We can learn a graph structure without prior knowledge

Forecasting is a widely used technique in both industry and science

Key Components Time Convolution (TC) Module Time Convolution The temporal convolution is …

The Root Relative Squared Error (RSE) is an evaluation metric in time series forecasting,1 $$ …

The Continuous Ranked Probability Score, known as CRPS, is a score to measure how a proposed …

What problem is StemGNN solving: intra-series temporal pattern: DFT Each series inter-series …