Abstract: Probabilistic forecasting of multivariate time series is essential for various downstream tasks. Most existing approaches rely on the sequences being uniformly spaced and aligned across all ...
Abstract: Multivariate time series (MTS) forecasting appears in many applied settings, ranging from finance and healthcare to energy systems, climate analysis, and IoT-based platforms. In these fields ...
If you find this repo useful, please cite our paper. @inproceedings{yi2023fouriergnn, title={Fourier{GNN}: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective}, author={Kun ...
A comprehensive data science project analyzing the famous Iris dataset with exploratory data analysis, statistical analysis, univariate/bivariate/multivariate ...
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