Chengbin Hou

Orcid: 0000-0001-6648-793X

According to our database1, Chengbin Hou authored at least 23 papers between 2018 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Learning to Generate Secure Code via Token-Level Rewards.
CoRR, February, 2026

Parse Trees Guided LLM Prompt Compression.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2026

KGC-Explainer: Toward Explainable Knowledge Graph Completion.
IEEE Trans. Reliab., 2026

2025
Enhancing Noise Robustness of Parkinson's Disease Telemonitoring via Contrastive Feature Augmentation.
CoRR, October, 2025

Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs.
IEEE Trans. Neural Networks Learn. Syst., March, 2025

FedAGHN: Personalized federated learning with attentive graph hypernetworks.
Knowl. Based Syst., 2025

Node importance estimation leveraging LLMs for semantic augmentation in knowledge graphs.
Knowl. Based Syst., 2025

Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023
Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews.
CoRR, 2023

2022
Network embedding and its applications.
PhD thesis, 2022

GloDyNE: Global Topology Preserving Dynamic Network Embedding.
IEEE Trans. Knowl. Data Eng., 2022

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.
CoRR, 2022

Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift.
CoRR, 2022

GloDyNE: Global Topology Preserving Dynamic Network Embedding (Extended Abstract).
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021
Robust Dynamic Network Embedding via Ensembles.
CoRR, 2021

Towards Robust Dynamic Network Embedding.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

A Network Embedding Based Approach to Drug-Target Interaction Prediction Using Additional Implicit Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020
RoSANE: Robust and scalable attributed network embedding for sparse networks.
Neurocomputing, 2020

2019
DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding.
CoRR, 2019

Learning Topological Representation for Networks via Hierarchical Sampling.
Proceedings of the International Joint Conference on Neural Networks, 2019

2018
Attributed Network Embedding for Incomplete Structure Information.
CoRR, 2018


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