Graph neural networks in recommender systems: a survey S Wu, F Sun, W Zhang*, X Xie, B Cui* ACM Computing Surveys 55 (5), 1-37, 2022 | 945 | 2022 |
Diffusion models: A comprehensive survey of methods and applications L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, Y Shao, W Zhang*, ... ACM Computing Surveys, 2022 | 823 | 2022 |
Graph attention multi-layer perceptron W Zhang, Z Yin, Z Sheng, Y Li, W Ouyang, X Li, Y Tao, Z Yang, B Cui ACM SIGKDD 2022, 2022 | 112* | 2022 |
OpenBox: A Generalized Black-box Optimization Service Y Li, Y Shen, W Zhang, Y Chen, H Jiang, M Liu, J Jiang, J Gao, W Wu, ... ACM SIGKDD 2021, 2021 | 69 | 2021 |
Reliable data distillation on graph convolutional network W Zhang, X Miao, Y Shao, J Jiang, L Chen, O Ruas, B Cui ACM SIGMOD 2020, 1399-1414, 2020 | 67 | 2020 |
GPT4Rec: A generative framework for personalized recommendation and user interests interpretation J Li, W Zhang, T Wang, G Xiong, A Lu, G Medioni arXiv preprint arXiv:2304.03879, 2023 | 62 | 2023 |
Model Degradation Hinders Deep Graph Neural Networks W Zhang, Z Sheng, Z Yin, Y Jiang, Y Xia, J Gao, Z Yang, B Cui ACM SIGKDD 2022, 2022 | 61* | 2022 |
Snapshot boosting: a fast ensemble framework for deep neural networks W Zhang, J Jiang, Y Shao, B Cui Science China Information Sciences 63 (1), 112102, 2020 | 59 | 2020 |
Node Dependent Local Smoothing for Scalable Graph Learning W Zhang, M Yang, Z Sheng, Y Li, W Ouyang, Y Tao, Z Yang, B Cui NeurIPS 2021, Spotlight Paper (Acceptance Rate < 3%), 2021 | 52 | 2021 |
PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm W Zhang, Y Shen, Z Lin, Y Li, X Li, W Ouyang, Y Tao, Z Yang, B Cui WWW 2022, Best Student Paper Award, 2022 | 43 | 2022 |
VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition Y Li, Y Shen, W Zhang, C Zhang, B Cui The VLDB Journal 32 (2), 389-413, 2023 | 41 | 2023 |
DeGNN: Improving Graph Neural Networks with Graph Decomposition X Miao, NM Gürel, W Zhang, Z Han, B Li, W Min, SX Rao, H Ren, Y Shan, ... ACM SIGKDD 2021, 1223-1233, 2021 | 38* | 2021 |
Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization W Zhang, Z Yang, Y Wang, Y Shen, Y Li, L Wang, B Cui VLDB 2021, 2021 | 35 | 2021 |
Lasagne: A multi-layer graph convolutional network framework via node-aware deep architecture X Miao, W Zhang, Y Shao, B Cui, L Chen, C Zhang, J Jiang IEEE Transactions on Knowledge and Data Engineering 2021, 2021 | 33 | 2021 |
Diffusion-based scene graph to image generation with masked contrastive pre-training L Yang, Z Huang, Y Song, S Hong, G Li, W Zhang, B Cui, B Ghanem, ... arXiv preprint arXiv:2211.11138, 2022 | 32 | 2022 |
Alg: Fast and accurate active learning framework for graph convolutional networks W Zhang, Y Shen, Y Li, L Chen, Z Yang, B Cui ACM SIGMOD 2021, 2366-2374, 2021 | 31 | 2021 |
ROD: reception-aware online distillation for sparse graphs W Zhang, Y Jiang, Y Li, Z Sheng, Y Shen, X Miao, L Wang, Z Yang, B Cui ACM SIGKDD 2021, 2232-2242, 2021 | 24 | 2021 |
Transfer learning for Bayesian optimization: A survey T Bai, Y Li, Y Shen, X Zhang, W Zhang, B Cui arXiv preprint arXiv:2302.05927, 2023 | 23 | 2023 |
Distributed graph neural network training: A survey Y Shao, H Li, X Gu, H Yin, Y Li, X Miao, W Zhang, B Cui, L Chen ACM Computing Surveys, 2022 | 22 | 2022 |
ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies Y Shen, Y Li, J Zheng, W Zhang, P Yao, J Li, S Yang, J Liu, B Cui AAAI 2023, 2021 | 21 | 2021 |