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Found 2 papers, 2 papers with code
Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation
Also, graph-like optical flow, dynamic graphs, and missing impact can be obtained naturally by HSPGNN, which provides better dynamic analysis and explanation than traditional data-driven models.
Multivariate Time Series Imputation
Optical Flow Estimation
+1
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting
Also, by F1-score and probability distribution analysis, we demonstrate that DVGNN better reflects the causal relationship and uncertainty of dynamic graphs.
