| A Novel Ensemble Method for Imbalanced Data Learning: Bagging of Extrapolation‐SMOTE SVM Q Wang, ZH Luo, JC Huang, YH Feng, Z Liu Computational intelligence and neuroscience 2017 (1), 1827016, 2017 | 171 | 2017 |
| Drug target protein‐protein interaction networks: a systematic perspective Y Feng, Q Wang, T Wang BioMed research international 2017 (1), 1289259, 2017 | 111 | 2017 |
| CSAN: A neural network benchmark model for crime forecasting in spatio-temporal scale Q Wang, G Jin, X Zhao, Y Feng, J Huang Knowledge-Based Systems 189, 105120, 2020 | 52 | 2020 |
| A novel framework for the identification of drug target proteins: Combining stacked auto-encoders with a biased support vector machine Q Wang, YH Feng, JC Huang, TJ Wang, GQ Cheng PloS one 12 (4), e0176486, 2017 | 43 | 2017 |
| Doubly stochastic variational inference for neural processes with hierarchical latent variables Q Wang, H Van Hoof ICML 2020, 2020 | 34 | 2020 |
| Urban Fire Situation Forecasting: Deep sequence learning with spatio-temporal dynamics G Jin, Q Wang, C Zhu, Y Feng, J Huang, X Hu Applied Soft Computing 97, 106730, 2020 | 22 | 2020 |
| Model-based meta reinforcement learning using graph structured surrogate models and amortized policy search Q Wang, H Van Hoof ICML 2022 Spotlight, 2022 | 20 | 2022 |
| Crime-GAN: A context-based sequence generative network for crime forecasting with adversarial loss G Jin, Q Wang, X Zhao, Y Feng, Q Cheng, J Huang 2019 IEEE International Conference on Big Data (Big Data), 1460-1469, 2019 | 19 | 2019 |
| 多 Agent 深度强化学习综述 梁星星， 冯旸赫， 马扬， 程光权， 黄金才， 王琦， 周玉珍， 刘忠 自动化学报 46 (12), 2537-2557, 2020 | 17 | 2020 |
| On the improvement of reinforcement active learning with the involvement of cross entropy to address one-shot learning problem H Huang, J Huang, Y Feng, J Zhang, Z Liu, Q Wang, L Chen PloS one 14 (6), e0217408, 2019 | 16 | 2019 |
| Learning expressive meta-representations with mixture of expert neural processes Q Wang, H van Hoof NeurIPS 2022, 2022 | 12 | 2022 |
| Novel deep reinforcement learning algorithm based on attention-based value function and autoregressive environment model 梁星星， 冯旸赫， 黄金才， 王琦， 马扬， 刘忠 Journal of Software 31 (4), 948-966, 2020 | 12 | 2020 |
| Bridge the Inference Gaps of Neural Processes via Expectation Maximization Q Wang, M Federici, H van Hoof ICLR 2023, 2023 | 8 | 2023 |
| Episodic Multi-Task Learning with Heterogeneous Neural Processes J Shen, X Zhen, C Wang, M Worring NeurIPS 2023 Spotlight, 2023 | 4 | 2023 |
| Large-scale generative simulation artificial intelligence: The next hotspot Q Wang, Y Feng, J Huang, Y Lv, Z Xie, X Gao The Innovation 4 (6), 2023 | 2 | 2023 |
| A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm Q Wang, Y Lv, Y Feng, Z Xie, J Huang NeurIPS 2023, 2023 | 2 | 2023 |
| GO4Align: Group Optimization for Multi-Task Alignment J Shen, C Wang, Z Xiao, N Van Noord, M Worring arXiv preprint arXiv:2404.06486, 2024 | 1 | 2024 |
| Non-informative noise-enhanced stochastic neural networks for improving adversarial robustness H Yang, M Wang, Q Wang, Z Yu, G Jin, C Zhou, Y Zhou Information Fusion 108, 102397, 2024 | | 2024 |
| Balanced Confidence Calibration for Graph Neural Networks H Yang, M Wang, Q Wang, M Lao, Y Zhou KDD 2024, 2024 | | 2024 |
| Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation Y Yang, Y Shi, C Wang, X Zhen, Y Shi, J Xu ICML 2024, 2024 | | 2024 |
