Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting B Yu, H Yin, Z Zhu Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 4451 | 2018 |
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks H Wang, H Yin, M Zhang, P Li ICLR 2022, 2022 | 124 | 2022 |
St-unet: A spatio-temporal u-network for graph-structured time series modeling B Yu, H Yin, Z Zhu arXiv preprint arXiv:1903.05631, 2019 | 78 | 2019 |
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning H Yin, M Zhang, Y Wang, J Wang, P Li Proceedings of the VLDB Endowment 15 (11), 2788 - 2796, 2022 | 43 | 2022 |
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective R Wei, H Yin, J Jia, AR Benson, P Li NeurIPS 2022, 2022 | 29 | 2022 |
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning H Yin, M Zhang, J Wang, P Li Proceedings of the VLDB Endowment 16 (11), 2939 - 2948, 2023 | 11 | 2023 |
Revisiting graph neural networks and distance encoding from a practical view H Yin, Y Wang, P Li AAAI 2021, DLG workshop, 2020 | 8 | 2020 |
Semantic analysis of spatial temporal trajectory in LBSNs H YIN, Y LIU Scientia Sinica (Informationis) 47 (8), 1051-1065, 2017 | 4 | 2017 |
On the inherent privacy properties of discrete denoising diffusion models R Wei, E Kreačić, H Wang, H Yin, E Chien, VK Potluru, P Li Transaction on Machine Learning Research, 2024 | 3 | 2024 |
OCTAL: Graph Representation Learning for LTL Model Checking P Mukherjee, H Yin, S Suresh, T Rompf KDD 2023, DLG workshop (Contributed Talk), 2022 | 2 | 2022 |
SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents W Xiang, H Yin, H Wang, X Jin Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024 | 1 | 2024 |
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models H Yin, R Wei, E Chien, P Li arXiv preprint arXiv:2410.08299, 2024 | | 2024 |
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures T Zhang, H Yin, R Wei, P Li, A Shrivastava Proceedings of the ACM Web Conference 2024, 2023 | | 2023 |