Jiafeng Lin

TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts

Multimodal time series forecasting has garnered significant attention for its potential to provide more robust and accurate predictions than traditional single-modality models by leveraging rich information inherent in other modalities. However, due to fundamental challenges in modality alignment, e…