Hengyu Liu
This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.
Known people with the same name:
- Hengyu Liu 001 (Northeastern University, Shenyang, China)
- Hengyu Liu 002 (Beijing Jiaotong University, Beijing, China)
- Hengyu Liu 003 (Wuhan University of Science and Technology, Wuhan, China)
- Hengyu Liu 004 (Hangzhou Normal University, Hangzhou, China)
- Hengyu Liu 005 (Xiamen University, Xiamen, China)
- Hengyu Liu 006 (Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang, China)
- Hengyu Liu 007 (Chinese University of Hong Kong, Hong Kong)
Bibliography
2025
SIP Flooding Attack Detection Technology of Multi-agent System Covert Network Based on BiGRU Algorithm.
Int. J. Comput. Intell. Syst., December, 2025
MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data (Extended Version).
CoRR, July, 2025
CoRR, July, 2025
WonderFree: Enhancing Novel View Quality and Cross-View Consistency for 3D Scene Exploration.
CoRR, June, 2025
Considering the multi-time scale rolling optimization scheduling method of micro-energy network connected to electric vehicles.
CoRR, June, 2025
LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment.
CoRR, June, 2025
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise.
CoRR, January, 2025
FlexGS: Train Once, Deploy Everywhere with Many-in-One Flexible 3D Gaussian Splatting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025
2024
Open capacity of distribution network including distributed power supply and network reconfiguration.
Intell. Decis. Technol., 2024
Provably Extending PageRank-based Local Clustering Algorithm to Weighted Directed Graphs with Self-Loops and to Hypergraphs.
CoRR, 2024
Hypergraphs as Weighted Directed Self-Looped Graphs: Spectral Properties, Clustering, Cheeger Inequality.
CoRR, 2024
Integrating Online Learning with Collaborative Machine Learning for Continuous Intrusion Detection in SDN.
Proceedings of the IEEE Conference on Network Function Virtualization and Software Defined Networks, 2024