Jan 1, 2025
Jan 1, 2025
By dynamically retrieving relevant information from an external knowledge base, our TimeRAF enhances prediction accuracy, leading to more precise zero-shot forecasting performance.
Dec 30, 2024
We propose the Local-Global Representation Alignment framework (LogoRA), which combines multi-scale convolutional and transformer encoders, integrates representations with a fusion module, and employs advanced alignment strategies, achieving state-of-the-art performance on four time-series datasets.
Sep 30, 2024