| Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs M Chen, W Zhang, W Zhang, Q Chen, H Chen EMNLP 2019, 4217-4226, 2019 | 208 | 2019 |
| FedE: Embedding Knowledge Graphs in Federated Setting M Chen, W Zhang, Z Yuan, Y Jia, H Chen IJCKG 2021, 80-88, 2021 | 51 | 2021 |
| Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding M Chen, W Zhang, Y Zhu, H Zhou, Z Yuan, C Xu, H Chen SIGIR 2022, 927-937, 2022 | 49 | 2022 |
| Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting M Chen, W Zhang, Z Yao, X Chen, M Ding, F Huang, H Chen IJCAI 2022, 1966-1972, 2022 | 23 | 2022 |
| Relational Message Passing for Fully Inductive Knowledge Graph Completion Y Geng, J Chen, W Zhang, JZ Pan, M Chen, H Chen, S Jiang ICDE 2023, 1697–1707, 2022 | 23 | 2022 |
| DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning Y Zhu, W Zhang, M Chen, H Chen, X Cheng, W Zhang, H Chen WSDM 2022, 1516-1524, 2022 | 21 | 2022 |
| Federated knowledge graph completion via embedding-contrastive learning M Chen, W Zhang, Z Yuan, Y Jia, H Chen Knowledge-Based Systems 252, 109459, 2022 | 16 | 2022 |
| Generalizing to Unseen Elements: A Survey on Knowledge Extrapolation for Knowledge Graphs M Chen, W Zhang, Y Geng, Z Xu, JZ Pan, H Chen IJCAI 2023, 2023 | 15 | 2023 |
| Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer W Zhang, Y Zhu, M Chen, Y Geng, Y Huang, Y Xu, W Song, H Chen WWW 2023, 2581-2590, 2023 | 12 | 2023 |
| Tele-Knowledge Pre-training for Fault Analysis Z Chen, W Zhang, Y Huang, M Chen, Y Geng, H Yu, Z Bi, Y Zhang, Z Yao, ... ICDE 2023, 2022 | 12 | 2022 |
| Understanding and Improving Knowledge Graph Embedding for Entity Alignment L Guo, Q Zhang, Z Sun, M Chen, W Hu, H Chen ICML 2022, 8145-8156, 2022 | 12 | 2022 |
| Knowledge Graph Embedding in E-commerce Applications: Attentive Reasoning, Explanations, and Transferable Rules W Zhang, S Deng, M Chen, L Wang, Q Chen, F Xiong, X Liu, H Chen IJCKG 2021, 71-79, 2021 | 11 | 2021 |
| NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs W Zhang, X Chen, Z Yao, M Chen, Y Zhu, H Yu, Y Huang, Y Xu, N Zhang, ... SIGIR 2022, 3323-3328, 2022 | 10 | 2022 |
| Analogical inference enhanced knowledge graph embedding Z Yao, W Zhang, M Chen, Y Huang, Y Yang, H Chen AAAI 2023 37 (4), 4801-4808, 2023 | 6 | 2023 |
| Modality-Aware Negative Sampling for Multi-modal Knowledge Graph Embedding Y Zhang, M Chen, W Zhang IJCNN 2023, 2023 | 6 | 2023 |
| A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning L Jin, Z Yao, M Chen, H Chen, W Zhang International Semantic Web Conference, 290-308, 2023 | 2 | 2023 |
| Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding M Chen, W Zhang, Z Yao, Y Zhu, Y Gao, JZ Pan, H Chen AAAI 2023, 2023 | 2 | 2023 |
| Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph Embedding X Chen, W Zhang, Z Yao, M Chen, S Tang International Semantic Web Conference, 253-270, 2023 | 1 | 2023 |
| NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learning W Zhang, Z Yao, M Chen, Z Huang, H Chen SIGIR 2023, 2023 | 1 | 2023 |
Wen ZhangZhejiang UniversityZweryfikowany adres z zju.edu.cn
