| Transferrable prototypical networks for unsupervised domain adaptation Y Pan, T Yao, Y Li, Y Wang, CW Ngo, T Mei Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 262 | 2019 |
| Artificial intelligence in breast imaging EPV Le, Y Wang, Y Huang, S Hickman, FJ Gilbert Clinical radiology 74 (5), 357-366, 2019 | 161 | 2019 |
| Connections with robust PCA and the role of emergent sparsity in variational autoencoder models B Dai, Y Wang, J Aston, G Hua, D Wipf The Journal of Machine Learning Research 19 (1), 1573-1614, 2018 | 62 | 2018 |
| Simultaneous Bayesian sparse approximation with structured sparse models W Chen, D Wipf, Y Wang, Y Liu, IJ Wassell IEEE Transactions on Signal Processing 64 (23), 6145-6159, 2016 | 52 | 2016 |
| Joint Contrastive Learning with Infinite Possibilities Q Cai *, Y Wang *, Y Pan, T Yao, T Mei NeurIPS 2020 spotlight, 2020 | 41 | 2020 |
| Learning a unified sample weighting network for object detection Q Cai, Y Pan, Y Wang, J Liu, T Yao, T Mei Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 27 | 2020 |
| Multi-task learning for subspace segmentation Y Wang, D Wipf, Q Ling, W Chen, I Wassell Proceedings of the 32nd International Conference on Machine Learning, 2015 | 20 | 2015 |
| A style and semantic memory mechanism for domain generalization Y Chen, Y Wang, Y Pan, T Yao, X Tian, T Mei Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 11 | 2021 |
| Recurrent variational autoencoders for learning nonlinear generative models in the presence of outliers Y Wang, B Dai, G Hua, J Aston, D Wipf IEEE Journal of Selected Topics in Signal Processing 12 (6), 1615-1627, 2018 | 10 | 2018 |
| Dual vision transformer T Yao, Y Li, Y Pan, Y Wang, XP Zhang, T Mei arXiv preprint arXiv:2207.04976, 2022 | 9 | 2022 |
| Transferrable contrastive learning for visual domain adaptation Y Chen, Y Pan, Y Wang, T Yao, X Tian, T Mei Proceedings of the 29th ACM International Conference on Multimedia, 3399-3408, 2021 | 8 | 2021 |
| Clustered Sparse Bayesian Learning. Y Wang, DP Wipf, JM Yun, W Chen, IJ Wassell The Conference on Uncertainty in Artificial Intelligence, 2015 | 7 | 2015 |
| Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration Y Wang, J Lin, J Zou, Y Pan, T Yao, T Mei Advances in Neural Information Processing Systems 34, 2021 | 5 | 2021 |
| Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders. Y Wang, B Dai, G Hua, J Aston, DP Wipf The Conference on Uncertainty in Artificial Intelligence, 2017 | 5 | 2017 |
| Exploiting the convex-concave penalty for tracking: A novel dynamic reweighted sparse Bayesian learning algorithm Y Wang, D Wipf, W Chen, IJ Wassell 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 5 | 2014 |
| A low rank promoting prior for unsupervised contrastive learning Y Wang, J Lin, Q Cai, Y Pan, T Yao, H Chao, T Mei IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 4 | 2022 |
| Veiled attributes of the variational autoencoder B Dai, Y Wang, J Aston, G Hua, D Wipf arXiv preprint arXiv:1706.05148, 2017 | 2 | 2017 |
| SPE-Net: Boosting Point Cloud Analysis via Rotation Robustness Enhancement Z Qiu, Y Li, Y Wang, Y Pan, T Yao, T Mei Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 1 | 2022 |
| Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization J Lin, Y Wang, Q Cai, Y Pan, T Yao, H Chao, T Mei arXiv preprint arXiv:2209.12807, 2022 | 1 | 2022 |
| Sparse Bayesian Multitask Learning for Subspace Segmentation, Woman in Computer Vision Workshop in, IEEE Conference on Computer Vision and Pattern Recognition Yu Wang, David Wipf, John Aston Woman in Computer Vision Workshop in, IEEE Conference on Computer Vision and …, 2017 | | 2017 |
Wei ChenUniversity of Cambridge (PhD, Postdoc), Professor of Beijing Jiaotong University, ChinaVerified email at bjtu.edu.cn
