| Transfer learning of graph neural networks with ego-graph information maximization Q Zhu, C Yang, Y Xu, H Wang, C Zhang, J Han Advances in Neural Information Processing Systems 34, 1766-1779, 2021 | 87 | 2021 |
| Relation learning on social networks with multi-modal graph edge variational autoencoders C Yang, J Zhang, H Wang, S Li, M Kim, M Walker, Y Xiao, J Han Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 48 | 2020 |
| Augmentation-free graph contrastive learning with performance guarantee H Wang, J Zhang, Q Zhu, W Huang arXiv preprint arXiv:2204.04874, 2022 | 47 | 2022 |
| A neural corpus indexer for document retrieval Y Wang, Y Hou, H Wang, Z Miao, S Wu, Q Chen, Y Xia, C Chi, G Zhao, ... Advances in Neural Information Processing Systems 35, 25600-25614, 2022 | 45 | 2022 |
| Secure deep graph generation with link differential privacy C Yang, H Wang, K Zhang, L Chen, L Sun arXiv preprint arXiv:2005.00455, 2020 | 38* | 2020 |
| Deep active learning by leveraging training dynamics H Wang, W Huang, Z Wu, H Tong, AJ Margenot, J He Advances in Neural Information Processing Systems 35, 25171-25184, 2022 | 21 | 2022 |
| From intrinsic to counterfactual: On the explainability of contextualized recommender systems Y Zhou*, H Wang*, J He, H Wang arXiv preprint arXiv:2110.14844, 2021 | 15 | 2021 |
| Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph H Wang, J Zhang, Q Zhu, W Huang, K Kawaguchi, X Xiao Transactions on Machine Learning Research, 2023, 2023 | 10* | 2023 |
| Training fair deep neural networks by balancing influence H Wang*, Z Wu*, J He arXiv preprint arXiv:2201.05759, 2022 | 10 | 2022 |
| Neural concept map generation for effective document classification with interpretable structured summarization C Yang, J Zhang, H Wang, B Li, J Han Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 10 | 2020 |
| Understanding programmatic weak supervision via source-aware influence function J Zhang*, H Wang*, CY Hsieh, AJ Ratner Advances in Neural Information Processing Systems 35, 2862-2875, 2022 | 8 | 2022 |
| Subclass-balancing contrastive learning for long-tailed recognition C Hou, J Zhang, H Wang, T Zhou Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 7 | 2023 |
| Controllable gradient item retrieval H Wang, C Zhou, C Yang, H Yang, J He Proceedings of the Web Conference 2021, 768-777, 2021 | 7 | 2021 |
| Graph neural networks provably benefit from structural information: A feature learning perspective W Huang, Y Cao, H Wang, X Cao, T Suzuki arXiv preprint arXiv:2306.13926, 2023 | 6 | 2023 |
| The stronger the diffusion model, the easier the backdoor: Data poisoning to induce copyright breaches without adjusting finetuning pipeline H Wang, Q Shen, Y Tong, Y Zhang, K Kawaguchi arXiv preprint arXiv:2401.04136, 2024 | 5 | 2024 |
| Efficient Dataset Distillation via Minimax Diffusion J Gu, S Vahidian, V Kungurtsev, H Wang, W Jiang, Y You, Y Chen arXiv preprint arXiv:2311.15529, 2023 | 5 | 2023 |
| Model-enhanced Vector Index H Zhang, Y Wang, Q Chen, R Chang, T Zhang, Z Miao, Y Hou, Y Ding, ... Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| Complexity matters: Rethinking the latent space for generative modeling T Hu, F Chen, H Wang, J Li, W Wang, J Sun, Z Li Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| Leveraging relational graph neural network for transductive model ensemble Z Hu, J Zhang, H Wang, S Liu, S Liang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 4 | 2023 |
| Boosting visual-language models by exploiting hard samples H Wang, M Huang, R Huang, L Hong, H Xu, T Hu, X Liang, Z Li arXiv preprint arXiv:2305.05208, 2023 | 4 | 2023 |
