Rpmixer: Shaking up time series forecasting with random projections for large spatial-temporal data
Spatial-temporal forecasting systems play a crucial role in addressing numerous real-world
challenges. In this paper, we investigate the potential of addressing spatial-temporal …
challenges. In this paper, we investigate the potential of addressing spatial-temporal …
Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting
Traffic forecasting is crucial for intelligent transportation systems (ITS), aiding in efficient
resource allocation and effective traffic control. However, its effectiveness often relies heavily …
resource allocation and effective traffic control. However, its effectiveness often relies heavily …
Frequency Enhanced Pre-training for Cross-city Few-shot Traffic Forecasting
Abstract The field of Intelligent Transportation Systems (ITS) relies on accurate traffic
forecasting to enable various downstream applications. However, developing cities often …
forecasting to enable various downstream applications. However, developing cities often …
Scalable Transformer for High Dimensional Multivariate Time Series Forecasting
Deep models for Multivariate Time Series (MTS) forecasting have recently demonstrated
significant success. Channel-dependent models capture complex dependencies that …
significant success. Channel-dependent models capture complex dependencies that …
Traffic Forecasting Using Spatio-Temporal Dynamics and Multimodal Attention with Graph Attention Pdes
G Almousa, Y Lee - Available at SSRN 5031413 - papers.ssrn.com
Accurate traffic forecasting is essential for optimizing intelligent transportation systems, yet
many existing models struggle to capture the complex spatio-temporal dynamics inherent in …
many existing models struggle to capture the complex spatio-temporal dynamics inherent in …