Zhiqi Shao

Orcid: 0000-0002-8854-9799

According to our database1, Zhiqi Shao authored at least 22 papers between 2022 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Bias Mitigation in Large Language Models for Tabular Data Classification.
Mach. Learn., April, 2026

Toward an Integrated Cross-Urban Accident Prevention System: A Multi-Task Spatial-Temporal Learning Framework for Urban Safety Management.
CoRR, January, 2026

Unleashing Mamba's expressive power: A non-tradeoff approach to spatio-temporal forecasting.
Inf. Fusion, 2026

Diffusion denoised and physics-regularized inter-series model for long-horizon multivariate time-series forecasting.
Inf. Fusion, 2026

2025
STPFormer: A State-of-the-Art Pattern-Aware Spatio-Temporal Transformer for Traffic Forecasting.
CoRR, August, 2025

Frameless Graph Knowledge Distillation.
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.
Inf. Fusion, 2025

Revisiting time-varying dynamics in stock market forecasting: A multi-source sentiment analysis approach with large language model.
Decis. Support Syst., 2025

SVDformer: Direction-Aware Spectral Graph Embedding Learning via SVD and Transformer.
Proceedings of the AI 2025: Advances in Artificial Intelligence, 2025

2024
Enhancing framelet GCNs with generalized p-Laplacian regularization.
Int. J. Mach. Learn. Cybern., April, 2024

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion.
Trans. Mach. Learn. Res., 2024

STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting.
CoRR, 2024

ST-MambaSync: The Confluence of Mamba Structure and Spatio-Temporal Transformers for Precipitous Traffic Prediction.
CoRR, 2024

ST-SSMs: Spatial-Temporal Selective State of Space Model for Traffic Forecasting.
CoRR, 2024

CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model.
CoRR, 2024

2023
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond.
CoRR, 2023

How Curvature Enhance the Adaptation Power of Framelet GCNs.
CoRR, 2023

Frameless Graph Knowledge Distillation.
CoRR, 2023

Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion.
CoRR, 2023

A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models.
Proceedings of the Asian Conference on Machine Learning, 2023

2022
Generalized Laplacian Regularized Framelet GCNs.
CoRR, 2022

Generalized energy and gradient flow via graph framelets.
CoRR, 2022


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