Yanshen Sun

Orcid: 0000-0001-6048-2978

According to our database1, Yanshen Sun authored at least 26 papers between 2014 and 2025.

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

Timeline

2014
2016
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2020
2022
2024
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Legend:

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In proceedings 
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Links

On csauthors.net:

Bibliography

2025
Multi-granularity physicochemical-inspired molecular representation learning for property prediction.
Expert Syst. Appl., 2025

Integrating clinicopathologic information and dynamic contrast-enhanced MRI for augmented prediction of neoadjuvant chemotherapy response in breast cancer.
Biomed. Signal Process. Control., 2025

2024
BTSSPro: Prompt-Guided Multimodal Co-Learning for Breast Cancer Tumor Segmentation and Survival Prediction.
IEEE J. Biomed. Health Informatics, December, 2024

A Multi-Relational Graph Encoder Network for Fine-Grained Prediction of MiRNA-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2024

Sparse graph cascade multi-kernel fusion contrastive learning for microbe-disease association prediction.
Expert Syst. Appl., 2024

Downscaling Precipitation with Bias-informed Conditional Diffusion Model.
CoRR, 2024

PGDiffSeg: Prior-Guided Denoising Diffusion Model with Parameter-Shared Attention for Breast Cancer Segmentation.
CoRR, 2024

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction.
CoRR, 2024

Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challenges.
CoRR, 2024

Learning Decentralized Flocking Controllers with Spatio-Temporal Graph Neural Network.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Empowering Cross-Patient Epilepsy Diagnosis from Diverse-Sampling Low-Quality EEG Signals.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023
EMPPNet: Enhancing Molecular Property Prediction via Cross-modal Information Flow and Hierarchical Attention.
Expert Syst. Appl., December, 2023

Multi-View Graph Contrastive Learning via Adaptive Channel Optimization for Depression Detection in EEG Signals.
Int. J. Neural Syst., November, 2023

Dual Network Contrastive Learning for Predicting Microbe-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

Adaptive dual graph contrastive learning based on heterogeneous signed network for predicting adverse drug reaction.
Inf. Sci., 2023

Med-MMHL: A Multi-Modal Dataset for Detecting Human- and LLM-Generated Misinformation in the Medical Domain.
CoRR, 2023

DG-Trans: Dual-level Graph Transformer for Spatiotemporal Incident Impact Prediction on Traffic Networks.
CoRR, 2023

Infinitely Deep Graph Transformation Networks.
Proceedings of the IEEE International Conference on Data Mining, 2023

Spatial Temporal Graph Neural Networks for Decentralized Control of Robot Swarms.
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

RoadFormer: Road-Anchored Adversarial Dynamic Graph Transformer for Unlimited-Range Traffic Incident Impact Prediction.
Proceedings of the IEEE International Conference on Big Data, 2023

LightK-DSGCN: Depression Detection in EEGs with Lightweight Kalman Filter-aided Dual-Stream Graph Convolutional Networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
Detecting anomalous traffic behaviors with seasonal deep Kalman filter graph convolutional neural networks.
J. King Saud Univ. Comput. Inf. Sci., 2022

Twitter Bot Identification: An Anomaly Detection Approach.
Proceedings of the IEEE International Conference on Big Data, 2022

2020
The Scalability of X3D4 PointProperties: Benchmarks on WWW Performance.
Proceedings of the Web3D '20: The 25th International Conference on 3D Web Technology, 2020

2015
Dynamic Multi-relational Networks Integration and Extended Link Prediction Method.
Proceedings of the Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques, 2015

2014
Applying Bi-directional Link Mining in Personalized Recommendation.
J. Softw., 2014


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