publications

2023

  1. MEDFAIR: Benchmarking Fairness for Medical Imaging
    Yongshuo Zong, Yongxin Yang, and Timothy Hospedales
    In International Conference on Learning Representations (ICLR), 2023
  2. ChiroDiff: Modelling chirographic data with Diffusion Models
    Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, and Yi-Zhe Song
    In International Conference on Learning Representations (ICLR), 2023
  3. Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection
    Xiongjie Chen, Yunpeng Li, and Yongxin Yang
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
  4. Mixture of Normalizing Flows for European Option Pricing
    Yongxin Yang, and Timothy M Hospedales
    In Conference on Uncertainty in Artificial Intelligence (UAI), 2023
  5. Partial Index Tracking: A Meta-Learning Approach
    Yongxin Yang, and Timothy M Hospedales
    In Conference on Lifelong Learning Agents (CoLLAs), 2023
  6. On Calibration of Mathematical Finance Models by Hypernetworks
    Yongxin Yang, and Timothy M Hospedales
    In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2023
  7. Learning to Name Classes for Vision and Language Models
    Sarah Parisot, Yongxin Yang, and Steven McDonagh
    In Conference on Computer Vision and Pattern Recognition (CVPR), 2023
  8. An Evaluation of Self-Supervised Learning for Portfolio Diversification
    Yongxin Yang, and Timothy M Hospedales
    In International Conference on Artificial Neural Networks (ICANN), 2023
  9. Mixstyle neural networks for domain generalization and adaptation
    Kaiyang Zhou, Yongxin Yang, Yu Qiao, and Tao Xiang
    International Journal of Computer Vision, 2023
  10. Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error
    Ondrej Bohdal, Yongxin Yang, and Timothy Hospedales
    Transactions on Machine Learning Research (TMLR), 2023

2022

  1. PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning
    Zefu Chen, Yu Zheng, Yongxin Yang, Yingzhao Huang, Sen Zhao, Hengqiang Zhao, Chenxi Yu, and 4 more authors
    The American Journal of Human Genetics, 2022
  2. DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data
    Jiaqi Liu, Hengqiang Zhao, Yu Zheng, Lin Dong, Sen Zhao, Yukuan Huang, Shengkai Huang, and 4 more authors
    Genome Medicine, 2022
  3. Augmented sliced Wasserstein distances
    Xiongjie Chen, Yongxin Yang, and Yunpeng Li
    In International Conference on Learning Representations (ICLR), 2022
  4. SketchODE: Learning neural sketch representation in continuous time
    Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, and Yi-Zhe Song
    In International Conference on Learning Representations (ICLR), 2022
  5. Loss Function Learning for Domain Generalization by Implicit Gradient
    Boyan Gao, Henry Gouk, Yongxin Yang, and Timothy Hospedales
    In International Conference on Machine Learning (ICML), 2022
  6. Long-tail Recognition via Compositional Knowledge Transfer
    Sarah Parisot, Pedro M Esperança, Steven McDonagh, Tamas J Madarasz, Yongxin Yang, and Zhenguo Li
    In Computer Vision and Pattern Recognition (CVPR), 2022
  7. Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images
    Nanqing Dong, Matteo Maggioni, Yongxin Yang, Eduardo Pérez-Pellitero, Ales Leonardis, and Steven McDonagh
    In International Joint Conference on Artificial Intelligence (IJCAI), 2022
  8. ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
    Qishi Dong, Awais Muhammad, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, and 1 more author
    In Neural Information Processing Systems (NeurIPS), 2022
  9. Towards Unsupervised Sketch-based Image Retrieval
    Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M Hospedales, and Yi-Zhe Song
    In British Machine Vision Conference (BMVC), 2022

2021

  1. Domain adaptive ensemble learning
    Kaiyang Zhou, Yongxin Yang, Yu Qiao, and Tao Xiang
    IEEE Transactions on Image Processing, 2021
  2. Diagnostic yield and clinical impact of exome sequencing in early-onset scoliosis (EOS)
    Sen Zhao, Yuanqiang Zhang, Weisheng Chen, Weiyu Li, Shengru Wang, Lianlei Wang, Yanxue Zhao, and 4 more authors
    Journal of medical genetics, 2021
  3. Domain generalization with mixstyle
    Kaiyang Zhou, Yongxin Yang, Yu Qiao, and Tao Xiang
    In International Conference on Learning Representations (ICLR), 2021
  4. Learning generalisable omni-scale representations for person re-identification
    Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, and Tao Xiang
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
  5. Cloud2curve: Generation and vectorization of parametric sketches
    Ayan Das, Yongxin Yang, Timothy M Hospedales, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2021
  6. Vectorization and rasterization: Self-supervised learning for sketch and handwriting
    Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M Hospedales, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2021
  7. Dynamic multi-period sparse portfolio selection model with asymmetric investors’ sentiments
    Ju Wei, Yongxin Yang, Mingzhu Jiang, and Jianguo Liu
    Expert Systems with Applications, 2021
  8. Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction
    Yu Zheng, Yongxin Yang, and Bowei Chen
    In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
  9. More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
    Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Yongxin Yang, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2021
  10. Stylemeup: Towards style-agnostic sketch-based image retrieval
    Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2021
  11. Context-Aware Layout to Image Generation with Enhanced Object Appearance
    Sen He, Wentong Liao, Michael Ying Yang, Yongxin Yang, Yi-Zhe Song, Bodo Rosenhahn, and Tao Xiang
    In Computer Vision and Pattern Recognition (CVPR), 2021
  12. Simple and Effective Stochastic Neural Networks
    Tianyuan Yu, Yongxin Yang, Da Li, Timothy Hospedales, and Tao Xiang
    In AAAI Conference on Artificial Intelligence (AAAI), 2021
  13. Toward Fine-Grained Sketch-Based 3D Shape Retrieval
    Anran Qi, Yulia Gryaditskaya, Jifei Song, Yongxin Yang, Yonggang Qi, Timothy M Hospedales, Tao Xiang, and 1 more author
    IEEE Transactions on Image Processing, 2021
  14. Tensor Composition Net for Visual Relationship Prediction
    Yuting Qiang, Yongxin Yang, Yanwen Guo, and Timothy M Hospedales
    In British Machine Vision Conference (BMVC), 2021
  15. EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization
    Ondrej Bohdal, Yongxin Yang, and Timothy Hospedales
    In Neural Information Processing Systems (NeurIPS), 2021
  16. Fine-Grained VR Sketching: Dataset and Insights
    Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, and Yi-Zhe Song
    In International Conference on 3D Vision (3DV), 2021
  17. Towards Stochastic Neural Network via Feature Distribution Calibration
    Hao Yang, Min Wang, Yun Zhou, and Yongxin Yang
    In International Conference on Data Mining (ICDM), 2021
  18. Domain Attention Consistency for Multi-Source Domain Adaptation
    Zhongying Deng, Kaiyang Zhou, Yongxin Yang, and Tao Xiang
    In British Machine Vision Conference (BMVC), 2021

2020

  1. Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach
    Yu Zheng, Bowei Chen, Timothy M Hospedales, and Yongxin Yang
    In AAAI Conference on Artificial Intelligence (AAAI), 2020
  2. Diversity and Sparsity: A New Perspective on Index Tracking
    Yu Zheng, Timothy M Hospedales, and Yongxin Yang
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
  3. Deep clustering with concrete k-means
    Boyan Gao, Yongxin Yang, Henry Gouk, and Timothy M Hospedales
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
  4. DEEP CLUSTERING FOR DOMAIN ADAPTATION
    Boyan Gao, Yongxin Yang, Henry Gouk, and Timothy M Hospedales
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
  5. Deep Domain-Adversarial Image Generation for Domain Generalisation.
    Kaiyang Zhou, Yongxin Yang, Timothy M Hospedales, and Tao Xiang
    In AAAI Conference on Artificial Intelligence (AAAI), 2020
  6. Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval
    Kaiyue Pang, Yongxin Yang, Timothy M Hospedales, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2020
  7. Stochastic Classifiers for Unsupervised Domain Adaptation
    Zhihe Lu, Yongxin Yang, Xiatian Zhu, Cong Liu, Yi-Zhe Song, and Tao Xiang
    In Computer Vision and Pattern Recognition (CVPR), 2020
  8. Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval
    Ayan Kumar Bhunia, Yongxin Yang, Timothy M Hospedales, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2020
  9. Online Meta-Critic Learning for Off-Policy Actor-Critic Methods
    Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, and Timothy M Hospedales
    In Neural Information Processing Systems (NeurIPS), 2020
  10. DADA: Differentiable Automatic Data Augmentation
    Yonggang Li, Guosheng Hu, Yongtao Wang, Timothy Hospedales, Neil M Robertson, and Yongxin Yang
    In European Conference on Computer Vision (ECCV), 2020
  11. B\backslash’ezierSketch: A generative model for scalable vector sketches
    Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, and Yi-Zhe Song
    In European Conference on Computer Vision (ECCV), 2020
  12. Learning to Generate Novel Domains for Domain Generalization
    Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, and Tao Xiang
    In European Conference on Computer Vision (ECCV), 2020
  13. A Tree-Structured Decoder for Image-to-Markup Generation
    Jianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, Si Wei, and Lirong Dai
    In International Conference on Machine Learning (ICML), 2020
  14. Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval
    Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, and Yi-Zhe Song
    In British Machine Vision Conference (BMVC), 2020
  15. RelationNet2: Deep Comparison Network for Few-Shot Learning
    Xueting Zhang, Yuting Qiang, Flood Sung, Yongxin Yang, and Timothy M Hospedales
    In International Joint Conference on Neural Networks (IJCNN), 2020
  16. SRD: A Tree Structure Based Decoder for Online Handwritten Mathematical Expression Recognition
    Jianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, and Lirong Dai
    IEEE Transactions on Multimedia (TMM), 2020
  17. Pixelor: a competitive sketching AI agent. so you think you can sketch?
    Ayan Kumar Bhunia, Ayan Das, Umar Riaz Muhammad, Yongxin Yang, Timothy M Hospedales, Tao Xiang, Yulia Gryaditskaya, and 1 more author
    ACM Transactions on Graphics (TOG), 2020
  18. Sketch-a-Segmenter: Sketch-based Photo Segmenter Generation
    Conghui Hu, Da Li, Yongxin Yang, Timothy M Hospedales, and Yi-Zhe Song
    IEEE Transactions on Image Processing (TIP), 2020
  19. Towards 3D VR-Sketch to 3D Shape Retrieval
    Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, and Yi-Zhe Song
    In 2020 International Conference on 3D Vision (3DV), 2020
  20. Flexible Dataset Distillation: Learn Labels Instead of Images
    Ondrej Bohdal, Yongxin Yang, and Timothy Hospedales
    In Workshop on Meta-Learning, 2020
  21. Index tracking with differentiable asset selection
    Yu Zheng, Yunpeng Li, Qiuhua Xu, Timothy Hospedales, and Yongxin Yang
    In ACM International Conference on AI in Finance (ICAIF), 2020
  22. Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification
    Xiao Gong, Guosheng Hu, Timothy Hospedales, and Yongxin Yang
    In ECCV Workshop on Adversarial Robustness in Real World, 2020
  23. Sequential learning for domain generalization
    Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy Hospedales
    In TASK-CV Workshop at ECCV, 2020

2019

  1. Disjoint Label Space Transfer Learning with Common Factorised Space
    Xiaobin Chang, Yongxin Yang, Tao Xiang, and Timothy M Hospedales
    In AAAI Conference on Artificial Intelligence (AAAI), 2019
  2. Feature-Critic Networks for Heterogeneous Domain Generalization
    Yiying Li, Yongxin Yang, Wei Zhou, and Timothy M Hospedales
    In International Conference on Machine Learning (ICML), 2019
  3. Generalizable Person Re-identification by Domain-Invariant Mapping Network
    Jifei Song, Yongxin Yang, Yi-Zhe Song, Tao Xiang, and Timothy M Hospedales
    In Computer Vision and Pattern Recognition (CVPR), 2019
  4. Generalising Fine-Grained Sketch-Based Image Retrieval
    Kaiyue Pang, Ke Li, Yongxin Yang, Honggang Zhang, Timothy M Hospedales, Tao Xiang, and Yi-Zhe Song
    In Computer Vision and Pattern Recognition (CVPR), 2019
  5. Omni-Scale Feature Learning for Person Re-Identification
    Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, and Tao Xiang
    In International Conference on Computer Vision (ICCV), 2019
  6. Episodic training for domain generalization
    Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M Hospedales
    In International Conference on Computer Vision (ICCV), 2019
  7. Goal-Driven Sequential Data Abstraction
    Umar Riaz Muhammad, Yongxin Yang, Timothy M Hospedales, Tao Xiang, and Yi-Zhe Song
    In International Conference on Computer Vision (ICCV), 2019
  8. Robust Person Re-Identification by Modelling Feature Uncertainty
    Tianyuan Yu, Da Li, Yongxin Yang, Timothy M Hospedales, and Tao Xiang
    In International Conference on Computer Vision (ICCV), 2019

2018

  1. Deep Stock Representation Learning: From Candlestick Charts to Investment Decisions
    Guosheng Hu, Yuxin Hu, Kai Yang, Zehao Yu, Flood Sung, Zhihong Zhang, Fei Xie, and 4 more authors
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
  2. Learning to Generalize: Meta-Learning for Domain Generalization
    Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales
    In AAAI Conference on Artificial Intelligence (AAAI), 2018
  3. Learning to Compare: Relation Network for Few-Shot Learning
    Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip HS Torr, and Timothy M Hospedales
    In Computer Vision and Pattern Recognition (CVPR), 2018
  4. Learning Deep Sketch Abstraction
    Umar Riaz Muhammad, Yongxin Yang, Yi-Zhe Song, Tao Xiang, and Timothy M Hospedales
    In Computer Vision and Pattern Recognition (CVPR), 2018
  5. Deep Neural Decision Trees
    Yongxin Yang, Irene Garcia Morillo, and Timothy M Hospedales
    In ICML Workshop on Human Interpretability in Machine Learning (WHI), 2018
  6. Deep Multi-Task Learning to Recognise Subtle Facial Expressions of Mental States
    Guosheng Hu, Li Liu, Yang Yuan, Zehao Yu, Yang Hua, Zhihong Zhang, Fumin Shen, and 4 more authors
    In European Conference on Computer Vision (ECCV), 2018

2017

  1. Frankenstein: Learning Deep Face Representations using Small Data
    Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy Hospedales, and Jakob Verbeek
    IEEE Transactions on Image Processing (TIP), 2017
  2. Trace Norm Regularised Deep Multi-Task Learning
    Yongxin Yang, and Timothy M Hospedales
    In International Conference on Learning Representations (ICLR) Workshop, 2017
  3. Deep Multi-task Representation Learning: A Tensor Factorisation Approach
    Yongxin Yang, and Timothy Hospedales
    In International Conference on Learning Representations (ICLR), 2017
  4. Gated Neural Networks for Option Pricing: Rationality by Design
    Yongxin Yang, Yu Zheng, and Timothy M Hospedales
    In AAAI Conference on Artificial Intelligence (AAAI), 2017
  5. Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives
    Yongxin Yang, and Timothy M Hospedales
    In Domain Adaptation in Computer Vision Applications, 2017
  6. Spectroscopic super-resolution fluorescence cell imaging using ultra-small Ge quantum dots
    Mingying Song, Ali Karatutlu, Isma Ali, Osman Ersoy, Yun Zhou, Yongxin Yang, Yuanpeng Zhang, and 3 more authors
    Optics Express, 2017
  7. Learning to Learn: Meta-Critic Networks for Sample Efficient Learning
    Flood Sung, Li Zhang, Tao Xiang, Timothy Hospedales, and Yongxin Yang
    arXiv preprint arXiv:1706.09529, 2017
  8. Actor-Critic Sequence Training for Image Captioning
    Li Zhang, Flood Sung, Feng Liu, Tao Xiang, Shaogang Gong, Yongxin Yang, and Timothy M Hospedales
    In NIPS Workshop on Visually-Grounded Interaction and Language (ViGIL), 2017
  9. Deeper, Broader and Artier Domain Generalization
    Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales
    In International Conference on Computer Vision (ICCV), 2017
  10. Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks
    Guosheng Hu, Yang Hua, Yang Yuan, Zhihong Zhang, Zheng Lu, Sankha S Mukherjee, Timothy M Hospedales, and 2 more authors
    In International Conference on Computer Vision (ICCV), 2017

2016

  1. Sketch-a-Net: A Deep Neural Network that Beats Humans
    Qian Yu, Yongxin Yang, Feng Liu, Yi-Zhe Song, Tao Xiang, and Timothy M Hospedales
    International Journal of Computer Vision (IJCV), 2016
  2. Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes
    Zhiyuan Shi, Yongxin Yang, Timothy Hospedales, and Tao Xiang
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016
  3. Multivariate Regression on the Grassmannian for Predicting Novel Domains
    Yongxin Yang, and Timothy M Hospedales
    In Computer Vision and Pattern Recognition (CVPR), 2016

2015

  1. A Unified Perspective on Multi-Domain and Multi-Task Learning
    Yongxin Yang, and Timothy M Hospedales
    In International Conference on Learning Representations (ICLR), 2015
  2. Sketch-a-Net that Beats Humans
    Qian Yu, Yongxin Yang, Yi-Zhe Song, Tao Xiang, and Timothy M Hospedales
    In British Machine Vision Conference (BMVC), 2015
  3. When Face Recognition Meets With Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition
    Guosheng Hu, Yongxin Yang, Dong Yi, Josef Kittler, William Christmas, Stan Li, and Timothy Hospedales
    In ChaLearn Looking at People Workshop ICCV (ChaLearn LAP), 2015
  4. Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian
    Yongxin Yang, and Timothy Hospedales
    In International Workshop on Differential Geometry in Computer Vision (Diff-CV), 2015

2014

  1. Transductive Multi-label Zero-shot Learning
    Yanwei Fu, Yongxin Yang, Timothy Hospedales, Tao Xiang, and Shaogang Gong
    In British Machine Vision Conference (BMVC), 2014
  2. Weakly Supervised Learning of Objects, Attributes and Their Associations
    Zhiyuan Shi, Yongxin Yang, Timothy M Hospedales, and Tao Xiang
    In European Conference on Computer Vision (ECCV), 2014