| Layer-dependent importance sampling for training deep and large graph convolutional networks D Zou, Z Hu, Y Wang, S Jiang, Y Sun, Q Gu Advances in neural information processing systems 32, 2019 | 280 | 2019 |
| LLM-Rec: Personalized Recommendation via Prompting Large Language Models H Lyu, S Jiang, H Zeng, Q Wang, S Zhang, R Chen, C Leung, J Tang, ... arXiv preprint arXiv:2307.15780, 2023 | 30 | 2023 |
| HINTS: citation time series prediction for new publications via dynamic heterogeneous information network embedding S Jiang, B Koch, Y Sun Proceedings of the Web Conference 2021, 3158-3167, 2021 | 29 | 2021 |
| Deep learning of potential outcomes B Koch, T Sainburg, P Geraldo, S Jiang, Y Sun, JG Foster arXiv preprint arXiv:2110.04442, 2021 | 15 | 2021 |
| Estimating Causal Effects on Networked Observational Data via Representation Learning S Jiang, Y Sun Proceedings of the 31st ACM International Conference on Information …, 2022 | 12 | 2022 |
| Learning probabilities of causation from finite population data A Li, S Jiang, Y Sun, J Pearl arXiv preprint arXiv:2210.08453, 2022 | 7 | 2022 |
| CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems S Jiang, Z Huang, X Luo, Y Sun arXiv preprint arXiv:2306.11216, 2023 | 6 | 2023 |
| A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings S Jiang, Q Yao, Q Wang, Y Sun Proceedings of the ACM Web Conference 2023, 2467-2476, 2023 | 5 | 2023 |
| Unit selection: Learning benefit function from finite population data A Li, S Jiang, Y Sun, J Pearl arXiv preprint arXiv:2210.08203, 2022 | 5 | 2022 |
| Resprompt: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models S Jiang, Z Shakeri, A Chan, M Sanjabi, H Firooz, Y Xia, B Akyildiz, Y Sun, ... arXiv preprint arXiv:2310.04743, 2023 | 4 | 2023 |
| Care: Modeling interacting dynamics under temporal environmental variation X Luo, H Wang, Z Huang, H Jiang, A Gangan, S Jiang, Y Sun Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Bridging Self-Attention and Time Series Decomposition for Periodic Forecasting S Jiang, T Syed, X Zhu, J Levy, B Aronchik, Y Sun Proceedings of the 31st ACM International Conference on Information …, 2022 | 2 | 2022 |
| Chordal-GCN: Exploiting sparsity in training large-scale graph convolutional networks X Jiang, K Cheng, S Jiang, Y Sun | 1 | 2019 |
| On the Equivalence of Graph Convolution and Mixup X Han, H Zeng, Y Chen, S Nie, J Liu, K Narang, Z Shakeri, ... arXiv preprint arXiv:2310.00183, 2023 | | 2023 |
Yizhou SunAssociate Professor, Computer Science, UCLAVerified email at cs.ucla.edu
