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 forecasting has wide applications such as traffic flow prediction, supermarket commodity demand forecasting and etc., and a large number of forecasting models have ...

We propose a new way to construct instruments in a broad class of economic environments. In the economies we study, a few large firms, industries or countries account for an important share of ...

Figure 3. HED. The encoder (left) uses TSA layer and segment merging to capture dependency at different scales; the decoder (right) makes the final prediction by forecasting at each scale and adding ...