Linjiang Zhou

Orcid: 0000-0003-3886-1300

According to our database1, Linjiang Zhou authored at least 12 papers between 2021 and 2025.

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

2025
Exploration of applications with ChatGPT for green supply chain management.
Ann. Oper. Res., December, 2025

MDSAM:Memory-Driven Sparse Attention Matrix for LVLMs Hallucination Mitigation.
CoRR, June, 2025

Baseline Generation Method for HIDS Data Based on Manifold Learning.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2025

2024
Robust Frame-Level Detection for Deepfake Videos With Lightweight Bayesian Inference Weighting.
IEEE Internet Things J., April, 2024

Rethinking the Principle of Gradient Smooth Methods in Model Explanation.
CoRR, 2024

E<sup>2</sup>CFD: Towards Effective and Efficient Cost Function Design for Safe Reinforcement Learning via Large Language Model.
CoRR, 2024

Axiomatization of Gradient Smoothing in Neural Networks.
CoRR, 2024

Dynamic Splitting of Diffusion Models for Multivariate Time Series Anomaly Detection in a JointCloud Environment.
Proceedings of the Knowledge Science, Engineering and Management, 2024

ProDiffAD: Progressively Distilled Diffusion Models for Multivariate Time Series Anomaly Detection in JointCloud Environment.
Proceedings of the International Joint Conference on Neural Networks, 2024

AdaDiffAD: Adaptively Segmenting Diffusion Models for Time Series Anomaly Detection in Dynamic JointCloud Environment.
Proceedings of the 30th IEEE International Conference on Parallel and Distributed Systems, 2024

2022
Points2Shapelets: A Salience-Guided Shapelets Selection Approach to Time Series Classification.
Proceedings of the International Joint Conference on Neural Networks, 2022

2021
Salience-CAM: Visual Explanations from Convolutional Neural Networks via Salience Score.
Proceedings of the International Joint Conference on Neural Networks, 2021


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