Wentao Zhang (张文涛)
Wentao Zhang (张文涛)
Assistant Professor, Peking University
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 56 (8), 1-39, 2024
Retrieval-augmented generation for ai-generated content: A survey
P Zhao, H Zhang, Q Yu, Z Wang, Y Geng, F Fu, L Yang, W Zhang, B Cui
arXiv preprint arXiv:2402.19473, 2024
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
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
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