Yuchang Zhu

Orcid: 0000-0001-5474-5671

According to our database1, Yuchang Zhu authored at least 22 papers between 2020 and 2025.

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

Timeline

Legend:

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Links

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Bibliography

2025
Heterophily-Aware Representation Learning on Heterogeneous Graphs.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2025

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning.
CoRR, June, 2025

SaGIF: Improving Individual Fairness in Graph Neural Networks via Similarity Encoding.
CoRR, June, 2025

GT-SVQ: A Linear-Time Graph Transformer for Node Classification Using Spiking Vector Quantization.
CoRR, April, 2025

Are Large Language Models In-Context Graph Learners?
CoRR, February, 2025

Measuring Diversity in Synthetic Datasets.
CoRR, February, 2025

FairDLA: Improving the fairness-utility trade-off in graph neural networks via dual-level alignment.
Knowl. Based Syst., 2025

2024
FairAGG: Toward Fair Graph Neural Networks via Fair Aggregation.
IEEE Trans. Comput. Soc. Syst., October, 2024

Simple Scalable Multimodal Semantic Segmentation Model.
Sensors, January, 2024

Revisiting and Benchmarking Graph Autoencoders: A Contrastive Learning Perspective.
CoRR, 2024

Fair Graph Representation Learning via Sensitive Attribute Disentanglement.
Proceedings of the ACM on Web Conference 2024, 2024

The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Comprehensive Teacher-based Multi-task Model Train Using a Small Amount of Data.
Proceedings of the International Joint Conference on Neural Networks, 2024

Lane Detection Method Based on Deformable Linear Convolution.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
CLA: A self-supervised contrastive learning method for leaf disease identification with domain adaptation.
Comput. Electron. Agric., August, 2023

LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning.
CoRR, 2023

Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs.
CoRR, 2023

Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning.
CoRR, 2023

2022
A Smartphone-Based Six-DOF Measurement Method With Marker Detector.
IEEE Trans. Instrum. Meas., 2022

AutoMine: An Unmanned Mine Dataset.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2020
Multi-Camera-Based Universal Measurement Method for 6-DOF of Rigid Bodies in World Coordinate System.
Sensors, 2020


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