| 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 | 382 | 2019 |
| Artificial intelligence in breast imaging EPV Le, Y Wang, Y Huang, S Hickman, FJ Gilbert Clinical radiology 74 (5), 357-366, 2019 | 244 | 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 Journal of Machine Learning Research 19 (41), 1-42, 2018 | 81 | 2018 |
| Joint Contrastive Learning with Infinite Possibilities Q Cai *, Y Wang *, Y Pan, T Yao, T Mei NeurIPS 2020 spotlight, 2020 | 61 | 2020 |
| Dual vision transformer T Yao, Y Li, Y Pan, Y Wang, XP Zhang, T Mei IEEE transactions on pattern analysis and machine intelligence, 2023 | 59 | 2023 |
| 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 | 58 | 2016 |
| 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 | 43 | 2020 |
| 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 | 37 | 2021 |
| 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 | 23 | 2015 |
| 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 | 18 | 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 | 16 | 2018 |
| 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 45 (3), 2667-2681, 2022 | 12 | 2022 |
| 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 | 10 | 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 | 7 | 2017 |
| Out-of-distribution detection via conditional kernel independence model Y Wang, J Zou, J Lin, Q Ling, Y Pan, T Yao, T Mei Advances in Neural Information Processing Systems 35, 36411-36425, 2022 | 6 | 2022 |
| Spe-net: Boosting point cloud analysis via rotation robustness enhancement Z Qiu, Y Li, Y Wang, Y Pan, T Yao, T Mei European Conference on Computer Vision, 593-609, 2022 | 6 | 2022 |
| Clustered Sparse Bayesian Learning. Y Wang, DP Wipf, JM Yun, W Chen, IJ Wassell The Conference on Uncertainty in Artificial Intelligence, 2015 | 6 | 2015 |
| Boosting graph contrastive learning via graph contrastive saliency C Wei, Y Wang, B Bai, K Ni, D Brady, L Fang International conference on machine learning, 36839-36855, 2023 | 5 | 2023 |
| 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 |
| DartBlur: Privacy Preservation with Detection Artifact Suppression B Jiang, B Bai, H Lin, Y Wang, Y Guo, L Fang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
Tao MeiHiDream.ai; Fellow of CAE/IEEE/IAPRVerified email at hidream.ai
