IEEE

Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction

Recently, Graph Convolution Network (GCN) and Temporal Convolution Network (TCN) are introduced into traffic prediction and achieve state-of-the-art performance due to their good ability for modeling ...
IEEE

Heterogeneous Spatiotemporal Graph Convolution Network for Multi-Modal Wind-PV Power Collaborative Prediction

Abstract: Accurate and generalized collaborative prediction of multi-cluster renewable energy power generation is both an inevitable trend and urgent demand as the growth of multi-region ...
GitHub

ModernTCN (ICLR 2024 Spotlight)

Donghao Luo and Xue Wang. ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis. In International Conference on Learning Representations, 2024. [Our paper in OpenReview]. We ...
GitHub

CTRL-F: Pairing Convolution with Transformer for Image Classification via Multi-Level Feature Cross-Attention and Representation Learning Fusion

This is the official pytorch implementation of the CTRL-F paper. Abstract: Transformers have captured growing attention in computer vision, thanks to its large capacity and global processing ...