15 citations · 20 across the 2 of their papers we have counts for
3 papers
cs.LG2024★ 5 cited
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
Dingyi Zhuang, Yuheng Bu, Guang Wang +2
Quantifying uncertainty is crucial for robust and reliable predictions. However, existing spatiotemporal deep learning mostly focuses on deterministic prediction, overlooking the i…
cs.LG2021★ 15 cited
Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging
Yuankai Wu, Dingyi Zhuang, Mengying Lei +2
Spatiotemporal kriging is an important application in spatiotemporal data analysis, aiming to recover/interpolate signals for unsampled/unobserved locations based on observed signa…
cs.LG2020
Inductive Graph Neural Networks for Spatiotemporal Kriging
Yuankai Wu, Dingyi Zhuang, Aurelie Labbe +1
Time series forecasting and spatiotemporal kriging are the two most important tasks in spatiotemporal data analysis. Recent research on graph neural networks has made substantial p…