Zhiqi Shao

According to our database, Zhiqi Shao authored at least 16 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Frameless Graph Knowledge Distillation.

Dai Shi, Zhiqi Shao, Junbin Gao, Zhiyong Wang, Yi Guo

IEEE Trans. Neural Networks Learn. Syst., May, 2025

ST-MambaSync: Complement the power of Mamba and Transformer fusion for less computational cost in spatial-temporal traffic forecasting.

Zhiqi Shao, Ze Wang, Xusheng Yao, Michael G. H. Bell, Junbin Gao

Inf. Fusion, 2025

Revisiting time-varying dynamics in stock market forecasting: A multi-source sentiment analysis approach with large language model.

Zhiqi Shao, Xusheng Yao, Feng Chen, Ze Wang, Junbin Gao

Decis. Support Syst., 2025

2024

Enhancing framelet GCNs with generalized p-Laplacian regularization.

Zhiqi Shao, Dai Shi, Andi Han, Andrey Vasnev, Yi Guo, Junbin Gao

Int. J. Mach. Learn. Cybern., April, 2024

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion.

Dai Shi, Zhiqi Shao, Yi Guo, Qibin Zhao, Junbin Gao

Trans. Mach. Learn. Res., 2024

STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting.

Zhiqi Shao, Haoning Xi, Haohui Lu, Ze Wang, Michael G. H. Bell, Junbin Gao

CoRR, 2024

ST-MambaSync: The Confluence of Mamba Structure and Spatio-Temporal Transformers for Precipitous Traffic Prediction.

Zhiqi Shao, Xusheng Yao, Ze Wang, Junbin Gao

CoRR, 2024

ST-SSMs: Spatial-Temporal Selective State of Space Model for Traffic Forecasting.

Zhiqi Shao, Michael G. H. Bell, Ze Wang, D. Glenn Geers, Haoning Xi, Junbin Gao

CoRR, 2024

CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model.

Zhiqi Shao, Michael G. H. Bell, Ze Wang, D. Glenn Geers, Xusheng Yao, Junbin Gao

CoRR, 2024

2023

Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond.

Zhiqi Shao, Dai Shi, Andi Han, Yi Guo, Qibin Zhao, Junbin Gao

CoRR, 2023

How Curvature Enhance the Adaptation Power of Framelet GCNs.

Dai Shi, Yi Guo, Zhiqi Shao, Junbin Gao

CoRR, 2023

Frameless Graph Knowledge Distillation.

Dai Shi, Zhiqi Shao, Yi Guo, Junbin Gao

CoRR, 2023

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion.

Dai Shi, Zhiqi Shao, Yi Guo, Qibin Zhao, Junbin Gao

CoRR, 2023

A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models.

Dai Shi, Zhiqi Shao, Andi Han, Yi Guo, Junbin Gao

Proceedings of the Asian Conference on Machine Learning, 2023

2022

Generalized Laplacian Regularized Framelet GCNs.

Zhiqi Shao, Andi Han, Dai Shi, Andrey Vasnev, Junbin Gao

CoRR, 2022

Generalized energy and gradient flow via graph framelets.

Andi Han, Dai Shi, Zhiqi Shao, Junbin Gao

CoRR, 2022