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Yu Wang
Yu Wang
Statistical Lab, Department of Pure Mathematics and Statistics, University of Cambridge, UK
Verified email at cam.ac.uk
Title
Cited by
Cited by
Year
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
2622019
Artificial intelligence in breast imaging
EPV Le, Y Wang, Y Huang, S Hickman, FJ Gilbert
Clinical radiology 74 (5), 357-366, 2019
1612019
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
622018
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
522016
Joint Contrastive Learning with Infinite Possibilities
Q Cai *, Y Wang *, Y Pan, T Yao, T Mei
NeurIPS 2020 spotlight, 2020
412020
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
272020
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
202015
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
112021
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
102018
Dual vision transformer
T Yao, Y Li, Y Pan, Y Wang, XP Zhang, T Mei
arXiv preprint arXiv:2207.04976, 2022
92022
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
82021
Clustered Sparse Bayesian Learning.
Y Wang, DP Wipf, JM Yun, W Chen, IJ Wassell
The Conference on Uncertainty in Artificial Intelligence, 2015
72015
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
52021
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
52017
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
52014
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
42022
Veiled attributes of the variational autoencoder
B Dai, Y Wang, J Aston, G Hua, D Wipf
arXiv preprint arXiv:1706.05148, 2017
22017
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
12022
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
12022
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
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