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2020 – today
- 2024
[j18]Xiaoming Jiang
, Yongxin Yang, Tong Su, Kai Xiao, Lidan Lu, Wei Wang, Changsong Guo, Lizhi Shao, Mingjing Wang, Dong Jiang:
Unsupervised domain adaptation based on feature and edge alignment for femur X-ray image segmentation. Comput. Medical Imaging Graph. 116: 102407 (2024)- [j17]Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang:
MixStyle Neural Networks for Domain Generalization and Adaptation. Int. J. Comput. Vis. 132(3): 822-836 (2024) - [j16]Nanqing Dong, Linus Ericsson, Yongxin Yang, Ales Leonardis, Steven McDonagh:
Label-efficient object detection via region proposal network pre-training. Neurocomputing 577: 127376 (2024) - [c75]Yuanyuan Liu, Yongxin Yang:
Leveraging Stochastic Optimization in Asset Allocation for Enhanced Index Tracking. CIFEr 2024: 1-8 - [c74]Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Fei Chen, Steven McDonagh, Gerasimos Lampouras, Ignacio Iacobacci, Sarah Parisot:
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation. CVPR 2024: 22413-22422 - [c73]Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, Timothy M. Hospedales:
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models. ICML 2024 - [c72]Wei Dai, Yinghao Yao, Hengte Kong, Zhen Ji Chen, Sheng Wang, Qingshi Bai, Haojun Sun, Yongxin Yang, Jianzhong Su:
RIP-AV: Joint Representative Instance Pre-training with Context Aware Network for Retinal Artery/Vein Segmentation. MICCAI (1) 2024: 764-774 - [i66]Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, Timothy M. Hospedales:
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models. CoRR abs/2402.02207 (2024) - [i65]Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Fei Chen, Steven McDonagh, Gerasimos Lampouras, Ignacio Iacobacci, Sarah Parisot:
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation. CoRR abs/2404.02790 (2024) - [i64]Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Sarah Parisot:
Generating Compositional Scenes via Text-to-image RGBA Instance Generation. CoRR abs/2411.10913 (2024) - 2023
- [j15]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error. Trans. Mach. Learn. Res. 2023 (2023) - [c71]Yongxin Yang, Timothy M. Hospedales:
Partial Index Tracking: A Meta-Learning Approach. CoLLAs 2023: 415-436 - [c70]Sarah Parisot, Yongxin Yang, Steven McDonagh:
Learning to Name Classes for Vision and Language Models. CVPR 2023: 23477-23486 - [c69]Yongxin Yang, Timothy M. Hospedales:
An Evaluation of Self-supervised Learning for Portfolio Diversification. ICANN (3) 2023: 283-294 - [c68]Xiongjie Chen, Yunpeng Li, Yongxin Yang:
Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection. ICASSP 2023: 1-5 - [c67]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
ChiroDiff: Modelling chirographic data with Diffusion Models. ICLR 2023 - [c66]Yongshuo Zong, Yongxin Yang, Timothy M. Hospedales:
MEDFAIR: Benchmarking Fairness for Medical Imaging. ICLR 2023 - [c65]Yongxin Yang, Timothy M. Hospedales:
On Calibration of Mathematical Finance Models by Hypernetworks. ECML/PKDD (6) 2023: 227-242 - [c64]Yongxin Yang, Timothy M. Hospedales:
Mixture of Normalizing Flows for European Option Pricing. UAI 2023: 2390-2399 - [i63]Sarah Parisot, Yongxin Yang, Steven McDonagh:
Learning to Name Classes for Vision and Language Models. CoRR abs/2304.01830 (2023) - [i62]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
ChiroDiff: Modelling chirographic data with Diffusion Models. CoRR abs/2304.03785 (2023) - [i61]Bowen Li, Yongxin Yang, Steven McDonagh, Shifeng Zhang, Petru-Daniel Tudosiu, Sarah Parisot:
Optimisation-Based Multi-Modal Semantic Image Editing. CoRR abs/2311.16882 (2023) - [i60]Kaichen Zhou, Lanqing Hong, Enze Xie, Yongxin Yang, Zhenguo Li, Wei Zhang:
SERF: Fine-Grained Interactive 3D Segmentation and Editing with Radiance Fields. CoRR abs/2312.15856 (2023) - 2022
- [j14]Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang:
Learning Generalisable Omni-Scale Representations for Person Re-Identification. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5056-5069 (2022) - [j13]Jiansong Li, Xueying Wang, Xiaobing Chen, Guangli Li, Xiao Dong, Peng Zhao, Xianzhi Yu, Yongxin Yang, Wei Cao, Lei Liu, Xiaobing Feng:
An Application-oblivious Memory Scheduling System for DNN Accelerators. ACM Trans. Archit. Code Optim. 19(4): 47:1-47:26 (2022) - [c63]Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M. Hospedales, Yi-Zhe Song:
Towards Unsupervised Sketch-based Image Retrieval. BMVC 2022: 224 - [c62]Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li:
Long-tail Recognition via Compositional Knowledge Transfer. CVPR 2022: 6929-6938 - [c61]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
SketchODE: Learning neural sketch representation in continuous time. ICLR 2022 - [c60]Xiongjie Chen, Yongxin Yang, Yunpeng Li:
Augmented Sliced Wasserstein Distances. ICLR 2022 - [c59]Boyan Gao, Henry Gouk, Yongxin Yang, Timothy M. Hospedales:
Loss Function Learning for Domain Generalization by Implicit Gradient. ICML 2022: 7002-7016 - [c58]Nanqing Dong, Matteo Maggioni, Yongxin Yang, Eduardo Pérez-Pellitero, Ales Leonardis, Steven McDonagh:
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images. IJCAI 2022: 2930-2936 - [c57]Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li:
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. NeurIPS 2022 - [i59]Xiongjie Chen, Yunpeng Li, Yongxin Yang:
Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection. CoRR abs/2206.12911 (2022) - [i58]Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
Fine-Grained VR Sketching: Dataset and Insights. CoRR abs/2209.10008 (2022) - [i57]Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
Towards 3D VR-Sketch to 3D Shape Retrieval. CoRR abs/2209.10020 (2022) - [i56]Yongshuo Zong, Yongxin Yang, Timothy M. Hospedales:
MEDFAIR: Benchmarking Fairness for Medical Imaging. CoRR abs/2210.01725 (2022) - [i55]Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li:
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. CoRR abs/2210.09236 (2022) - [i54]Linus Ericsson, Nanqing Dong, Yongxin Yang, Ales Leonardis, Steven McDonagh:
Region Proposal Network Pre-Training Helps Label-Efficient Object Detection. CoRR abs/2211.09022 (2022) - 2021
- [j12]Ju Wei, Yongxin Yang, Mingzhu Jiang, Jianguo Liu:
Dynamic multi-period sparse portfolio selection model with asymmetric investors' sentiments. Expert Syst. Appl. 177: 114945 (2021) - [j11]Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang:
Domain Adaptive Ensemble Learning. IEEE Trans. Image Process. 30: 8008-8018 (2021) - [j10]Anran Qi, Yulia Gryaditskaya, Jifei Song, Yongxin Yang, Yonggang Qi, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Toward Fine-Grained Sketch-Based 3D Shape Retrieval. IEEE Trans. Image Process. 30: 8595-8606 (2021) - [j9]Jianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, Lirong Dai:
SRD: A Tree Structure Based Decoder for Online Handwritten Mathematical Expression Recognition. IEEE Trans. Multim. 23: 2471-2480 (2021) - [c56]Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
Fine-Grained VR Sketching: Dataset and Insights. 3DV 2021: 1003-1013 - [c55]Tianyuan Yu, Yongxin Yang, Da Li, Timothy M. Hospedales, Tao Xiang:
Simple and Effective Stochastic Neural Networks. AAAI 2021: 3252-3260 - [c54]Zhongying Deng, Kaiyang Zhou, Yongxin Yang, Tao Xiang:
Domain Attention Consistency for Multi-Source Domain Adaptation. BMVC 2021: 4 - [c53]Yuting Qiang, Yongxin Yang, Xueting Zhang, Yanwen Guo, Timothy M. Hospedales:
Tensor Composition Net for Visual Relationship Prediction. BMVC 2021: 434 - [c52]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
More Photos Are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval. CVPR 2021: 4247-4256 - [c51]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. CVPR 2021: 5672-5681 - [c50]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Cloud2Curve: Generation and Vectorization of Parametric Sketches. CVPR 2021: 7088-7097 - [c49]Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval. CVPR 2021: 8504-8513 - [c48]Sen He, Wentong Liao, Michael Ying Yang, Yongxin Yang, Yi-Zhe Song, Bodo Rosenhahn, Tao Xiang:
Context-Aware Layout to Image Generation With Enhanced Object Appearance. CVPR 2021: 15049-15058 - [c47]Hao Yang, Min Wang, Yun Zhou, Yongxin Yang:
Towards Stochastic Neural Network via Feature Distribution Calibration. ICDM 2021: 1445-1450 - [c46]Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang:
Domain Generalization with MixStyle. ICLR 2021 - [c45]Jiansong Li, Xiao Dong, Guangli Li, Peng Zhao, Xueying Wang, Xiaobing Chen, Xianzhi Yu, Yongxin Yang, Zihan Jiang, Wei Cao, Lei Liu, Xiaobing Feng:
Pinpointing the Memory Behaviors of DNN Training. ISPASS 2021: 217-219 - [c44]Yu Zheng, Yongxin Yang, Bowei Chen:
Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction. KDD 2021: 3968-3975 - [c43]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. NeurIPS 2021: 22234-22246 - [i53]Sen He, Wentong Liao, Michael Ying Yang, Yongxin Yang, Yi-Zhe Song, Bodo Rosenhahn, Tao Xiang:
Context-Aware Layout to Image Generation with Enhanced Object Appearance. CoRR abs/2103.11897 (2021) - [i52]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. CoRR abs/2103.13716 (2021) - [i51]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval. CoRR abs/2103.13990 (2021) - [i50]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Cloud2Curve: Generation and Vectorization of Parametric Sketches. CoRR abs/2103.15536 (2021) - [i49]Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval. CoRR abs/2103.15706 (2021) - [i48]Jiansong Li, Xiao Dong, Guangli Li, Peng Zhao, Xueying Wang, Xiaobing Chen, Xianzhi Yu, Yongxin Yang, Zihan Jiang, Wei Cao, Lei Liu, Xiaobing Feng:
Pinpointing the Memory Behaviors of DNN Training. CoRR abs/2104.00258 (2021) - [i47]Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang:
Domain Generalization with MixStyle. CoRR abs/2104.02008 (2021) - [i46]Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M. Hospedales, Yi-Zhe Song:
Towards Unsupervised Sketch-based Image Retrieval. CoRR abs/2105.08237 (2021) - [i45]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error. CoRR abs/2106.09613 (2021) - [i44]Nanqing Dong, Matteo Maggioni, Yongxin Yang, Eduardo Pérez-Pellitero, Ales Leonardis, Steven McDonagh:
Residual Contrastive Learning for Joint Demosaicking and Denoising. CoRR abs/2106.10070 (2021) - [i43]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. CoRR abs/2106.10575 (2021) - [i42]Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang:
MixStyle Neural Networks for Domain Generalization and Adaptation. CoRR abs/2107.02053 (2021) - [i41]Zhongying Deng, Kaiyang Zhou, Yongxin Yang, Tao Xiang:
Domain Attention Consistency for Multi-Source Domain Adaptation. CoRR abs/2111.03911 (2021) - [i40]Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li:
Long-tail Recognition via Compositional Knowledge Transfer. CoRR abs/2112.06741 (2021) - 2020
- [j8]Conghui Hu, Da Li, Yongxin Yang, Timothy M. Hospedales, Yi-Zhe Song:
Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation. IEEE Trans. Image Process. 29: 9470-9481 (2020) - [j7]Ayan Kumar Bhunia, Ayan Das, Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yulia Gryaditskaya, Yi-Zhe Song:
Pixelor: a competitive sketching AI agent. so you think you can sketch? ACM Trans. Graph. 39(6): 166:1-166:15 (2020) - [c42]Ling Luo, Yulia Gryaditskaya, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
Towards 3D VR-Sketch to 3D Shape Retrieval. 3DV 2020: 81-90 - [c41]Yu Zheng, Bowei Chen, Timothy M. Hospedales, Yongxin Yang:
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach. AAAI 2020: 1242-1249 - [c40]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Deep Domain-Adversarial Image Generation for Domain Generalisation. AAAI 2020: 13025-13032 - [c39]Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval. BMVC 2020 - [c38]Zhihe Lu, Yongxin Yang, Xiatian Zhu, Cong Liu, Yi-Zhe Song, Tao Xiang:
Stochastic Classifiers for Unsupervised Domain Adaptation. CVPR 2020: 9108-9117 - [c37]Ayan Kumar Bhunia, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval. CVPR 2020: 9776-9785 - [c36]Kaiyue Pang, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval. CVPR 2020: 10344-10352 - [c35]Xiao Gong, Guosheng Hu, Timothy M. Hospedales, Yongxin Yang:
Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification. ECCV Workshops (1) 2020: 135-151 - [c34]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Learning to Generate Novel Domains for Domain Generalization. ECCV (16) 2020: 561-578 - [c33]Yonggang Li, Guosheng Hu, Yongtao Wang, Timothy M. Hospedales, Neil Martin Robertson, Yongxin Yang:
Differentiable Automatic Data Augmentation. ECCV (22) 2020: 580-595 - [c32]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Sequential Learning for Domain Generalization. ECCV Workshops (1) 2020: 603-619 - [c31]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
BézierSketch: A Generative Model for Scalable Vector Sketches. ECCV (26) 2020: 632-647 - [c30]Yu Zheng, Yunpeng Li, Qiuhua Xu, Timothy M. Hospedales, Yongxin Yang:
Index tracking with differentiate asset selection. ICAIF 2020: 12:1-12:8 - [c29]Yu Zheng, Timothy M. Hospedales, Yongxin Yang:
Diversity and Sparsity: A New Perspective on Index Tracking. ICASSP 2020: 1768-1772 - [c28]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep Clustering for Domain Adaptation. ICASSP 2020: 4247-4251 - [c27]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep Clusteringwith Concrete K-Means. ICASSP 2020: 4252-4256 - [c26]Jianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, Si Wei, Lirong Dai:
A Tree-Structured Decoder for Image-to-Markup Generation. ICML 2020: 11076-11085 - [c25]Xueting Zhang, Yuting Qiang, Flood Sung, Yongxin Yang, Timothy M. Hospedales:
RelationNet2: Deep Comparison Network for Few-Shot Learning. IJCNN 2020: 1-8 - [c24]Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, Timothy M. Hospedales:
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods. NeurIPS 2020 - [i39]Ayan Kumar Bhunia, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Sketch Less for More: On-the-Fly Fine-Grained Sketch Based Image Retrieval. CoRR abs/2002.10310 (2020) - [i38]Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, Timothy M. Hospedales:
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods. CoRR abs/2003.05334 (2020) - [i37]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Deep Domain-Adversarial Image Generation for Domain Generalisation. CoRR abs/2003.06054 (2020) - [i36]Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang:
Domain Adaptive Ensemble Learning. CoRR abs/2003.07325 (2020) - [i35]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Sequential Learning for Domain Generalization. CoRR abs/2004.01377 (2020) - [i34]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Flexible Dataset Distillation: Learn Labels Instead of Images. CoRR abs/2006.08572 (2020) - [i33]Xiongjie Chen, Yongxin Yang, Yunpeng Li:
Augmented Sliced Wasserstein Distances. CoRR abs/2006.08812 (2020) - [i32]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
BézierSketch: A generative model for scalable vector sketches. CoRR abs/2007.02190 (2020) - [i31]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Learning to Generate Novel Domains for Domain Generalization. CoRR abs/2007.03304 (2020) - [i30]Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, Yi-Zhe Song:
Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval. CoRR abs/2007.15103 (2020) - [i29]Yuting Qiang, Yongxin Yang, Yanwen Guo, Timothy M. Hospedales:
Tensor Composition Net for Visual Relationship Prediction. CoRR abs/2012.05473 (2020)
2010 – 2019
- 2019
- [j6]Xin Zhang, Zhigang Chu, Yang Yang, Shuyi Zhao, Yongxin Yang:
An Alternative Hybrid Time-Frequency Domain Approach Based on Fast Iterative Shrinkage-Thresholding Algorithm for Rotating Acoustic Source Identification. IEEE Access 7: 59797-59805 (2019) - [j5]Xuemei Sun, Yongxin Yang, Maode Ma:
Minimum Connected Dominating Set Algorithms for Ad Hoc Sensor Networks. Sensors 19(8): 1919 (2019) - [c23]Xiaobin Chang, Yongxin Yang, Tao Xiang, Timothy M. Hospedales:
Disjoint Label Space Transfer Learning with Common Factorised Space. AAAI 2019: 3288-3295 - [c22]Kaiyue Pang, Ke Li, Yongxin Yang, Honggang Zhang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Generalising Fine-Grained Sketch-Based Image Retrieval. CVPR 2019: 677-686 - [c21]Jifei Song, Yongxin Yang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Generalizable Person Re-Identification by Domain-Invariant Mapping Network. CVPR 2019: 719-728 - [c20]Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Goal-Driven Sequential Data Abstraction. ICCV 2019: 71-80 - [c19]Tianyuan Yu, Da Li, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Robust Person Re-Identification by Modelling Feature Uncertainty. ICCV 2019: 552-561 - [c18]Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, Timothy M. Hospedales:
Episodic Training for Domain Generalization. ICCV 2019: 1446-1455 - [c17]Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang:
Omni-Scale Feature Learning for Person Re-Identification. ICCV 2019: 3701-3711 - [c16]Yiying Li, Yongxin Yang, Wei Zhou, Timothy M. Hospedales:
Feature-Critic Networks for Heterogeneous Domain Generalization. ICML 2019: 3915-3924 - [i28]Yiying Li, Yongxin Yang, Wei Zhou, Timothy M. Hospedales:
Feature-Critic Networks for Heterogeneous Domain Generalization. CoRR abs/1901.11448 (2019) - [i27]Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, Timothy M. Hospedales:
Episodic Training for Domain Generalization. CoRR abs/1902.00113 (2019) - [i26]Yu Zheng, Yongxin Yang, Bowei Chen:
Gated deep neural networks for implied volatility surfaces. CoRR abs/1904.12834 (2019) - [i25]Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang:
Omni-Scale Feature Learning for Person Re-Identification. CoRR abs/1905.00953 (2019) - [i24]Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Goal-Driven Sequential Data Abstraction. CoRR abs/1907.12336 (2019) - [i23]Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang:
Learning Generalisable Omni-Scale Representations for Person Re-Identification. CoRR abs/1910.06827 (2019) - [i22]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep clustering with concrete k-means. CoRR abs/1910.08031 (2019) - 2018
- [j4]Yongxin Yang, Rui Zhou, Yaojun Ge, Yanliang Du, Lihai Zhang:
Sensitivity Analysis of Geometrical Parameters on the Aerodynamic Performance of Closed-Box Girder Bridges. Sensors 18(7): 2053 (2018) - [j3]Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, Jakob Verbeek:
Frankenstein: Learning Deep Face Representations Using Small Data. IEEE Trans. Image Process. 27(1): 293-303 (2018) - [c15]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Learning to Generalize: Meta-Learning for Domain Generalization. AAAI 2018: 3490-3497 - [c14]Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H. S. Torr, Timothy M. Hospedales:
Learning to Compare: Relation Network for Few-Shot Learning. CVPR 2018: 1199-1208 - [c13]Umar Riaz Muhammad, Yongxin Yang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Learning Deep Sketch Abstraction. CVPR 2018: 8014-8023 - [c12]Guosheng Hu, Li Liu, Yang Yuan, Zehao Yu, Yang Hua, Zhihong Zhang, Fumin Shen, Ling Shao, Timothy M. Hospedales, Neil Martin Robertson, Yongxin Yang:
Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States. ECCV (12) 2018: 106-123 - [i21]Umar Riaz Muhammad, Yongxin Yang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Learning Deep Sketch Abstraction. CoRR abs/1804.04804 (2018) - [i20]Yongxin Yang, Irene Garcia Morillo, Timothy M. Hospedales:
Deep Neural Decision Trees. CoRR abs/1806.06988 (2018) - [i19]Xueting Zhang, Flood Sung, Yuting Qiang, Yongxin Yang, Timothy M. Hospedales:
Deep Comparison: Relation Columns for Few-Shot Learning. CoRR abs/1811.07100 (2018) - [i18]Xiaobin Chang, Yongxin Yang, Tao Xiang, Timothy M. Hospedales:
Disjoint Label Space Transfer Learning with Common Factorised Space. CoRR abs/1812.02605 (2018) - 2017
- [b1]Yongxin Yang:
Knowledge sharing: from atomic to parametrised context and shallow to deep models. Queen Mary University of London, UK, 2017 - [j2]Qian Yu, Yongxin Yang, Feng Liu, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Sketch-a-Net: A Deep Neural Network that Beats Humans. Int. J. Comput. Vis. 122(3): 411-425 (2017) - [j1]Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes. IEEE Trans. Pattern Anal. Mach. Intell. 39(12): 2525-2538 (2017) - [c11]Yongxin Yang, Yu Zheng, Timothy M. Hospedales:
Gated Neural Networks for Option Pricing: Rationality by Design. AAAI 2017: 52-58 - [c10]Guosheng Hu, Yang Hua, Yang Yuan, Zhihong Zhang, Zheng Lu, Sankha S. Mukherjee, Timothy M. Hospedales, Neil Martin Robertson, Yongxin Yang:
Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks. ICCV 2017: 3764-3773 - [c9]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Deeper, Broader and Artier Domain Generalization. ICCV 2017: 5543-5551 - [c8]Yongxin Yang, Timothy M. Hospedales:
Deep Multi-task Representation Learning: A Tensor Factorisation Approach. ICLR (Poster) 2017 - [c7]Yongxin Yang, Timothy M. Hospedales:
Trace Norm Regularised Deep Multi-Task Learning. ICLR (Workshop) 2017 - [p1]Yongxin Yang, Timothy M. Hospedales:
Unifying Multi-domain Multitask Learning: Tensor and Neural Network Perspectives. Domain Adaptation in Computer Vision Applications 2017: 291-309 - [i17]Flood Sung, Li Zhang, Tao Xiang, Timothy M. Hospedales, Yongxin Yang:
Learning to Learn: Meta-Critic Networks for Sample Efficient Learning. CoRR abs/1706.09529 (2017) - [i16]Li Zhang, Flood Sung, Feng Liu, Tao Xiang, Shaogang Gong, Yongxin Yang, Timothy M. Hospedales:
Actor-Critic Sequence Training for Image Captioning. CoRR abs/1706.09601 (2017) - [i15]Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Weakly Supervised Image Annotation and Segmentation with Objects and Attributes. CoRR abs/1708.02459 (2017) - [i14]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Deeper, Broader and Artier Domain Generalization. CoRR abs/1710.03077 (2017) - [i13]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Learning to Generalize: Meta-Learning for Domain Generalization. CoRR abs/1710.03463 (2017) - [i12]Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H. S. Torr, Timothy M. Hospedales:
Learning to Compare: Relation Network for Few-Shot Learning. CoRR abs/1711.06025 (2017) - 2016
- [c6]Yongxin Yang, Timothy M. Hospedales:
Multivariate Regression on the Grassmannian for Predicting Novel Domains. CVPR 2016: 5071-5080 - [i11]Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, Jakob Verbeek:
Frankenstein: Learning Deep Face Representations using Small Data. CoRR abs/1603.06470 (2016) - [i10]Yongxin Yang, Timothy M. Hospedales:
Deep Multi-task Representation Learning: A Tensor Factorisation Approach. CoRR abs/1605.06391 (2016) - [i9]Yongxin Yang, Timothy M. Hospedales:
Trace Norm Regularised Deep Multi-Task Learning. CoRR abs/1606.04038 (2016) - [i8]Yongxin Yang, Yu Zheng, Timothy M. Hospedales:
Gated Neural Networks for Option Pricing: Rationality by Design. CoRR abs/1609.07472 (2016) - [i7]Yongxin Yang, Timothy M. Hospedales:
Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives. CoRR abs/1611.09345 (2016) - 2015
- [c5]Qian Yu, Yongxin Yang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Sketch-a-Net that Beats Humans. BMVC 2015: 7.1-7.12 - [c4]Guosheng Hu, Yongxin Yang, Dong Yi, Josef Kittler, William J. Christmas, Stan Z. Li, Timothy M. Hospedales:
When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition. ICCV Workshops 2015: 384-392 - [c3]Yongxin Yang, Timothy M. Hospedales:
A Unified Perspective on Multi-Domain and Multi-Task Learning. ICLR (Poster) 2015 - [i6]Yongxin Yang, Timothy M. Hospedales:
Deep Neural Networks for Sketch Recognition. CoRR abs/1501.07873 (2015) - [i5]Yanwei Fu, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Shaogang Gong:
Transductive Multi-label Zero-shot Learning. CoRR abs/1503.07790 (2015) - [i4]Yanwei Fu, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Shaogang Gong:
Transductive Multi-class and Multi-label Zero-shot Learning. CoRR abs/1503.07884 (2015) - [i3]Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Weakly Supervised Learning of Objects, Attributes and their Associations. CoRR abs/1504.00045 (2015) - [i2]Guosheng Hu, Yongxin Yang, Dong Yi, Josef Kittler, William J. Christmas, Stan Z. Li, Timothy M. Hospedales:
When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition. CoRR abs/1504.02351 (2015) - [i1]Yongxin Yang, Timothy M. Hospedales:
Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian. CoRR abs/1507.07830 (2015) - 2014
- [c2]Yanwei Fu, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Shaogang Gong:
Transductive Multi-label Zero-shot Learning. BMVC 2014 - [c1]Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Weakly Supervised Learning of Objects, Attributes and Their Associations. ECCV (2) 2014: 472-487
Coauthor Index
[c73] [i66] [j15] [c71] [c69] [c67] [c66] [c65] [c64] [i62] [c63] [c61] [c59] [i56] [j10] [c55] [c53] [c51] [c50] [c43] [i52] [i50] [i46] [i45] [i43] [j8] [j7] [c41] [c40] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c25] [c24] [i39] [i38] [i37] [i35] [i34] [i32] [i31] [i29] [c23] [c22] [c21] [c20] [c19] [c18] [c16] [i28] [i27] [i24] [i22] [j3] [c15] [c14] [c13] [c12] [i21] [i20] [i19] [i18] [j2] [j1] [c11] [c10] [c9] [c8] [c7] [p1] [i17] [i16] [i15] [i14] [i13] [i12] [c6] [i11] [i10] [i9] [i8] [i7] [c5] [c4] [c3] [i6] [i5] [i4] [i3] [i2] [i1] [c2] [c1]
[j17] [c67] [i62] [j14] [c61] [i58] [i57] [j11] [j10] [c56] [c55] [c54] [c52] [c51] [c50] [c49] [c48] [c46] [i53] [i52] [i51] [i50] [i49] [i47] [i42] [i41] [j7] [c42] [c40] [c39] [c38] [c37] [c36] [c34] [c31] [i39] [i37] [i36] [i32] [i31] [i30] [c23] [c22] [c21] [c20] [c19] [c17] [i25] [i24] [i23] [c14] [c13] [i21] [i18] [j2] [j1] [i17] [i16] [i15] [i12] [c5] [i5] [i4] [i3] [c2] [c1]
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