Now You See Me: Deep Face Hallucination for Unviewed Sketches. - Conghui Hu; Da Li 001; Yi-Zhe Song; Timothy M. Hospedales (BMVC, 2017)

Deeper, Broader and Artier Domain Generalization. - Da Li 001; Yongxin Yang; Yi-Zhe Song; Timothy M. Hospedales (ICCV, 2017)

Learning to Generalize: Meta-Learning for Domain Generalization. - Da Li 001; Yongxin Yang; Yi-Zhe Song; Timothy M. Hospedales (AAAI, 2018)

Sketch-a-Classifier: Sketch-Based Photo Classifier Generation. - Conghui Hu; Da Li 001; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (CVPR, 2018)

Deep Factorised Inverse-Sketching. - Kaiyue Pang; Da Li 001; Jifei Song; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (ECCV (15), 2018)

Episodic Training for Domain Generalization. - Da Li 001; Jianshu Zhang 001; Yongxin Yang; Cong Liu 006; Yi-Zhe Song; Timothy M. Hospedales (ICCV, 2019)

Robust Person Re-Identification by Modelling Feature Uncertainty. - Tianyuan Yu; Da Li 001; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (ICCV, 2019)

Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation. - Da Li 001; Timothy M. Hospedales (ECCV (16), 2020)

Sequential Learning for Domain Generalization. - Da Li 001; Yongxin Yang; Yi-Zhe Song; Timothy M. Hospedales (ECCV Workshops (1), 2020)

A Stochastic Neural Network for Attack-Agnostic Adversarial Robustness. - Panagiotis Eustratiadis; Henry Gouk; Da Li 001; Timothy M. Hospedales (CoRR, 2020)

Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation. - Conghui Hu; Da Li 001; Yongxin Yang; Timothy M. Hospedales; Yi-Zhe Song (IEEE Trans. Image Process., 2020)

Simple and Effective Stochastic Neural Networks. - Tianyuan Yu; Yongxin Yang; Da Li 001; Timothy M. Hospedales; Tao Xiang 002 (AAAI, 2021)

A Simple Feature Augmentation for Domain Generalization. - Pan Li; Da Li 001; Wei Li 132; Shaogang Gong; Yanwei Fu 001; Timothy M. Hospedales (ICCV, 2021)

Weight-covariance alignment for adversarially robust neural networks. - Panagiotis Eustratiadis; Henry Gouk; Da Li 001; Timothy M. Hospedales (ICML, 2021)

A Channel Coding Benchmark for Meta-Learning. - Rui Li 052; Ondrej Bohdal; Rajesh K. Mishra; Hyeji Kim; Da Li 001; Nicholas D. Lane; Timothy M. Hospedales (NeurIPS Datasets and Benchmarks, 2021)

Robust Target Training for Multi-Source Domain Adaptation. - Zhongying Deng; Da Li 001; Yi-Zhe Song; Tao Xiang 002 (BMVC, 2022)

Learning to Augment via Implicit Differentiation for Domain Generalization. - Tingwei Wang; Da Li 001; Kaiyang Zhou; Tao Xiang 002; Yi-Zhe Song (BMVC, 2022)

Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. - Shell Xu Hu; Da Li 001; Jan Stühmer; Minyoung Kim 001; Timothy M. Hospedales (CVPR, 2022)

Fisher SAM: Information Geometry and Sharpness Aware Minimisation. - Minyoung Kim 001; Da Li 001; Shell Xu Hu; Timothy M. Hospedales (ICML, 2022)

Finding lost DG: Explaining domain generalization via model complexity. - Da Li 001; Henry Gouk; Timothy M. Hospedales (CoRR, 2022)

Feed-Forward Source-Free Latent Domain Adaptation via Cross-Attention. - Ondrej Bohdal; Da Li 001; Shell Xu Hu; Timothy M. Hospedales (CoRR, 2022)

A Simple Test-Time Method for Out-of-Distribution Detection. - Ke Fan; Yikai Wang 002; Qian Yu; Da Li 001; Yanwei Fu 001 (CoRR, 2022)

Attacking Adversarial Defences by Smoothing the Loss Landscape. - Panagiotis Eustratiadis; Henry Gouk; Da Li 001; Timothy M. Hospedales (CoRR, 2022)

Federated Learning for Inference at Anytime and Anywhere. - Zicheng Liu 006; Da Li 001; Javier Fernández-Marqués; Stefanos Laskaridis; Yan Gao 016; Lukasz Dudziak; Stan Z. Li; Shell Xu Hu; Timothy M. Hospedales (CoRR, 2022)

Dynamic Instance Domain Adaptation. - Zhongying Deng; Kaiyang Zhou; Da Li 001; Junjun He; Yi-Zhe Song; Tao Xiang 002 (IEEE Trans. Image Process., 2022)

Better Practices for Domain Adaptation. - Linus Ericsson; Da Li 001; Timothy M. Hospedales (AutoML, 2023)

Sketch-based Video Object Segmentation: Benchmark and Analysis. - Ruolin Yang 001; Da Li 001; Conghui Hu; Timothy M. Hospedales; Honggang Zhang 001; Yi-Zhe Song (BMVC, 2023)

Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. - Ondrej Bohdal; Yinbing Tian; Yongshuo Zong; Ruchika Chavhan; Da Li 001; Henry Gouk; Li Guo; Timothy M. Hospedales (CVPR, 2023)

Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. - Fengyin Lin; Mingkang Li 003; Da Li 001; Timothy M. Hospedales; Yi-Zhe Song; Yonggang Qi (CVPR, 2023)

Quality Diversity for Visual Pre-Training. - Ruchika Chavhan; Henry Gouk; Da Li 001; Timothy M. Hospedales (ICCV, 2023)

Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. - Minyoung Kim 001; Da Li 001; Timothy M. Hospedales (ICLR, 2023)

SketchKnitter: Vectorized Sketch Generation with Diffusion Models. - Qiang Wang; Haoge Deng; Yonggang Qi; Da Li 001; Yi-Zhe Song (ICLR, 2023)

FedL2P: Federated Learning to Personalize. - Royson Lee; Minyoung Kim 001; Da Li 001; Xinchi Qiu; Timothy M. Hospedales; Ferenc Huszar; Nicholas D. Lane (NeurIPS, 2023)

Generative Model Based Noise Robust Training for Unsupervised Domain Adaptation. - Zhongying Deng; Da Li 001; Junjun He; Yi-Zhe Song; Tao Xiang 002 (CoRR, 2023)

Feed-Forward Source-Free Domain Adaptation via Class Prototypes. - Ondrej Bohdal; Da Li 001; Timothy M. Hospedales (CoRR, 2023)

Label Calibration for Semantic Segmentation Under Domain Shift. - Ondrej Bohdal; Da Li 001; Timothy M. Hospedales (CoRR, 2023)

Prediction Calibration for Generalized Few-Shot Semantic Segmentation. - Zhihe Lu; Sen He 001; Da Li 001; Yi-Zhe Song; Tao Xiang 002 (IEEE Trans. Image Process., 2023)

Uncertainty-Aware Source-Free Domain Adaptive Semantic Segmentation. - Zhihe Lu; Da Li 001; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (IEEE Trans. Image Process., 2023)

Worst-case Feature Risk Minimization for Data-Efficient Learning. - Jingshi Lei; Da Li 001; Chengming Xu 001; Liming Fang; Timothy M. Hospedales; Yanwei Fu 001 (Trans. Mach. Learn. Res., 2023)

Neural Fine-Tuning Search for Few-Shot Learning. - Panagiotis Eustratiadis; Lukasz Dudziak; Da Li 001; Timothy M. Hospedales (ICLR, 2024)

Recurrent Early Exits for Federated Learning with Heterogeneous Clients. - Royson Lee; Javier Fernández-Marqués; Shell Xu Hu; Da Li 001; Stefanos Laskaridis; Lukasz Dudziak; Timothy M. Hospedales; Ferenc Huszár; Nicholas Donald Lane (ICML, 2024)

SketchAnimator: Animate Sketch via Motion Customization of Text-to-Video Diffusion Models. - Ruolin Yang 001; Da Li 001; Honggang Zhang 001; Yi-Zhe Song (VCIP, 2024)

Feed-Forward Latent Domain Adaptation. - Ondrej Bohdal; Da Li 001; Shell Xu Hu; Timothy M. Hospedales (WACV, 2024)

Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted. - Ruchika Chavhan; Ondrej Bohdal; Yongshuo Zong; Da Li 001; Timothy M. Hospedales (CoRR, 2024)

ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning. - Ruchika Chavhan; Da Li 001; Timothy M. Hospedales (ICLR, 2025)

Reserve to Adapt: Mining Inter-Class Relations for Open-Set Domain Adaptation. - Yujun Tong; Dongliang Chang; Da Li 001; Xinran Wang; Kongming Liang; Zhongjiang He; Yi-Zhe Song; Zhanyu Ma (IEEE Trans. Image Process., 2025)

HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models. - Young D. Kwon; Rui Li 052; Sijia Li; Da Li 001; Sourav Bhattacharya; Stylianos I. Venieris (CoRR, 2025)