Cross-city few-shot traffic forecasting via traffic pattern bank
Traffic forecasting is a critical service in Intelligent Transportation Systems (ITS). Utilizing
deep models to tackle this task relies heavily on data from traffic sensors or vehicle devices …
deep models to tackle this task relies heavily on data from traffic sensors or vehicle devices …
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
The field of Intelligent Transportation Systems (ITS) relies on accurate traffic forecasting to
enable various downstream applications. However, developing cities often face challenges …
enable various downstream applications. However, developing cities often face challenges …
Dataset Condensation for Time Series Classification via Dual Domain Matching
Time series data has been demonstrated to be crucial in various research fields. The
management of large quantities of time series data presents challenges in terms of deep …
management of large quantities of time series data presents challenges in terms of deep …
C-Mamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting
In recent years, significant progress has been made in multivariate time series forecasting
using Linear-based, Transformer-based, and Convolution-based models. However, these …
using Linear-based, Transformer-based, and Convolution-based models. However, these …