Da Li - RankMe

77 papers A* 21A 5C 1Journal 45Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BORT2: Bi-level optimization for robust target training in multi-source domain adaptation. Pattern Recognit. Zhongying Deng, Da Li, Xiaojiang Peng, Yi-Zhe Song, Tao Xiang
2026	J	`jnl`	Dynamic Expert Sharing: Decoupling Memory from Parallelism in Mixture-of-Experts Diffusion LLMs. CoRR Hao Mark Chen, Zhiwen Mo, Royson Lee, Qianzhou Wang, Da Li, Shell Xu Hu, Wayne Luk, Timothy M. Hospedales, Hongxiang Fan
2026	J	`jnl`	Generative models for noise-robust training in unsupervised domain adaptation. Pattern Recognit. Zhongying Deng, Da Li, Junjun He, Xiaojiang Peng, Yi-Zhe Song, Tao Xiang
2026	A*	`conf`	HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models. AAAI Young D. Kwon, Rui Li, Sijia Li, Da Li, Sourav Bhattacharya, Stylianos I. Venieris
2026	A*	`conf`	One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow. AAAI Zeyuan Wang, Da Li, Yulin Chen, Ye Shi, Liang Bai, Tianyuan Yu, Yanwei Fu
2025	A*	`conf`	ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning. ICLR Ruchika Chavhan, Da Li, Timothy M. Hospedales
2025	J	`jnl`	HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models. CoRR Young D. Kwon, Rui Li, Sijia Li, Da Li, Sourav Bhattacharya, Stylianos I. Venieris
2025	J	`jnl`	One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow. CoRR Zeyuan Wang, Da Li, Yulin Chen, Ye Shi, Liang Bai, Tianyuan Yu, Yanwei Fu
2025	J	`jnl`	Reserve to Adapt: Mining Inter-Class Relations for Open-Set Domain Adaptation. IEEE Trans. Image Process. Yujun Tong, Dongliang Chang, Da Li, Xinran Wang, Kongming Liang, Zhongjiang He, Yi-Zhe Song, Zhanyu Ma
2025	J	`jnl`	SketchAnimator: Animate Sketch via Motion Customization of Text-to-Video Diffusion Models. CoRR Ruolin Yang, Da Li, Honggang Zhang, Yi-Zhe Song
2024	J	`jnl`	ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning. CoRR Ruchika Chavhan, Da Li, Timothy M. Hospedales
2024	A	`conf`	Feed-Forward Latent Domain Adaptation. WACV Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales
2024	J	`jnl`	Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted. CoRR Ruchika Chavhan, Ondrej Bohdal, Yongshuo Zong, Da Li, Timothy M. Hospedales
2024	A*	`conf`	Neural Fine-Tuning Search for Few-Shot Learning. ICLR Panagiotis Eustratiadis, Lukasz Dudziak, Da Li, Timothy M. Hospedales
2024	A*	`conf`	Recurrent Early Exits for Federated Learning with Heterogeneous Clients. ICML Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas Donald Lane
2024	J	`jnl`	Recurrent Early Exits for Federated Learning with Heterogeneous Clients. CoRR Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2024	C	`conf`	SketchAnimator: Animate Sketch via Motion Customization of Text-to-Video Diffusion Models. VCIP Ruolin Yang, Da Li, Honggang Zhang, Yi-Zhe Song
2023	—	`conf`	Better Practices for Domain Adaptation. AutoML Linus Ericsson, Da Li, Timothy M. Hospedales
2023	J	`jnl`	Better Practices for Domain Adaptation. CoRR Linus Ericsson, Da Li, Timothy M. Hospedales
2023	A*	`conf`	Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. ICLR Minyoung Kim, Da Li, Timothy M. Hospedales
2023	J	`jnl`	Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. CoRR Minyoung Kim, Da Li, Timothy M. Hospedales
2023	A*	`conf`	FedL2P: Federated Learning to Personalize. NeurIPS Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane
2023	J	`jnl`	FedL2P: Federated Learning to Personalize. CoRR Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2023	J	`jnl`	Feed-Forward Source-Free Domain Adaptation via Class Prototypes. CoRR Ondrej Bohdal, Da Li, Timothy M. Hospedales
2023	J	`jnl`	Generative Model Based Noise Robust Training for Unsupervised Domain Adaptation. CoRR Zhongying Deng, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang
2023	J	`jnl`	Label Calibration for Semantic Segmentation Under Domain Shift. CoRR Ondrej Bohdal, Da Li, Timothy M. Hospedales
2023	A*	`conf`	Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CVPR Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales
2023	J	`jnl`	Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CoRR Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales
2023	J	`jnl`	Neural Fine-Tuning Search for Few-Shot Learning. CoRR Panagiotis Eustratiadis, Lukasz Dudziak, Da Li, Timothy M. Hospedales
2023	J	`jnl`	Prediction Calibration for Generalized Few-Shot Semantic Segmentation. IEEE Trans. Image Process. Zhihe Lu, Sen He, Da Li, Yi-Zhe Song, Tao Xiang
2023	A*	`conf`	Quality Diversity for Visual Pre-Training. ICCV Ruchika Chavhan, Henry Gouk, Da Li, Timothy M. Hospedales
2023	A	`conf`	Sketch-based Video Object Segmentation: Benchmark and Analysis. BMVC Ruolin Yang, Da Li, Conghui Hu, Timothy M. Hospedales, Honggang Zhang, Yi-Zhe Song
2023	J	`jnl`	Sketch-based Video Object Segmentation: Benchmark and Analysis. CoRR Ruolin Yang, Da Li, Conghui Hu, Timothy M. Hospedales, Honggang Zhang, Yi-Zhe Song
2023	A*	`conf`	SketchKnitter: Vectorized Sketch Generation with Diffusion Models. ICLR Qiang Wang, Haoge Deng, Yonggang Qi, Da Li, Yi-Zhe Song
2023	J	`jnl`	Uncertainty-Aware Source-Free Domain Adaptive Semantic Segmentation. IEEE Trans. Image Process. Zhihe Lu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
2023	J	`jnl`	Worst-case Feature Risk Minimization for Data-Efficient Learning. Trans. Mach. Learn. Res. Jingshi Lei, Da Li, Chengming Xu, Liming Fang, Timothy M. Hospedales, Yanwei Fu
2023	A*	`conf`	Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. CVPR Fengyin Lin, Mingkang Li, Da Li, Timothy M. Hospedales, Yi-Zhe Song, Yonggang Qi
2023	J	`jnl`	Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. CoRR Fengyin Lin, Mingkang Li, Da Li, Timothy M. Hospedales, Yi-Zhe Song, Yonggang Qi
2022	J	`jnl`	A Simple Test-Time Method for Out-of-Distribution Detection. CoRR Ke Fan, Yikai Wang, Qian Yu, Da Li, Yanwei Fu
2022	J	`jnl`	Attacking Adversarial Defences by Smoothing the Loss Landscape. CoRR Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales
2022	J	`jnl`	Dynamic Instance Domain Adaptation. CoRR Zhongying Deng, Kaiyang Zhou, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang
2022	J	`jnl`	Dynamic Instance Domain Adaptation. IEEE Trans. Image Process. Zhongying Deng, Kaiyang Zhou, Da Li, Junjun He, Yi-Zhe Song, Tao Xiang
2022	J	`jnl`	Federated Learning for Inference at Anytime and Anywhere. CoRR Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales
2022	J	`jnl`	Feed-Forward Source-Free Latent Domain Adaptation via Cross-Attention. CoRR Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales
2022	J	`jnl`	Finding lost DG: Explaining domain generalization via model complexity. CoRR Da Li, Henry Gouk, Timothy M. Hospedales
2022	A*	`conf`	Fisher SAM: Information Geometry and Sharpness Aware Minimisation. ICML Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales
2022	J	`jnl`	Fisher SAM: Information Geometry and Sharpness Aware Minimisation. CoRR Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales
2022	A	`conf`	Learning to Augment via Implicit Differentiation for Domain Generalization. BMVC Tingwei Wang, Da Li, Kaiyang Zhou, Tao Xiang, Yi-Zhe Song
2022	J	`jnl`	Learning to Augment via Implicit Differentiation for Domain Generalization. CoRR Tingwei Wang, Da Li, Kaiyang Zhou, Tao Xiang, Yi-Zhe Song
2022	J	`jnl`	Prediction Calibration for Generalized Few-shot Semantic Segmentation. CoRR Zhihe Lu, Sen He, Da Li, Yi-Zhe Song, Tao Xiang
2022	A*	`conf`	Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CVPR Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales
2022	J	`jnl`	Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CoRR Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales
2022	A	`conf`	Robust Target Training for Multi-Source Domain Adaptation. BMVC Zhongying Deng, Da Li, Yi-Zhe Song, Tao Xiang
2022	J	`jnl`	Robust Target Training for Multi-Source Domain Adaptation. CoRR Zhongying Deng, Da Li, Yi-Zhe Song, Tao Xiang
2021	—	`conf`	A Channel Coding Benchmark for Meta-Learning. NeurIPS Datasets and Benchmarks Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales
2021	J	`jnl`	A Channel Coding Benchmark for Meta-Learning. CoRR Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales
2021	A*	`conf`	A Simple Feature Augmentation for Domain Generalization. ICCV Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, Timothy M. Hospedales
2021	A*	`conf`	Simple and Effective Stochastic Neural Networks. AAAI Tianyuan Yu, Yongxin Yang, Da Li, Timothy M. Hospedales, Tao Xiang
2021	A*	`conf`	Weight-covariance alignment for adversarially robust neural networks. ICML Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales
2020	J	`jnl`	A Stochastic Neural Network for Attack-Agnostic Adversarial Robustness. CoRR Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales
2020	J	`jnl`	Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation. CoRR Da Li, Timothy M. Hospedales
2020	—	`conf`	Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation. ECCV (16) Da Li, Timothy M. Hospedales
2020	—	`conf`	Sequential Learning for Domain Generalization. ECCV Workshops (1) Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales
2020	J	`jnl`	Sequential Learning for Domain Generalization. CoRR Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales
2020	J	`jnl`	Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation. IEEE Trans. Image Process. Conghui Hu, Da Li, Yongxin Yang, Timothy M. Hospedales, Yi-Zhe Song
2019	A*	`conf`	Episodic Training for Domain Generalization. ICCV Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, Timothy M. Hospedales
2019	J	`jnl`	Episodic Training for Domain Generalization. CoRR Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, Timothy M. Hospedales
2019	A*	`conf`	Robust Person Re-Identification by Modelling Feature Uncertainty. ICCV Tianyuan Yu, Da Li, Yongxin Yang, Timothy M. Hospedales, Tao Xiang
2018	—	`conf`	Deep Factorised Inverse-Sketching. ECCV (15) Kaiyue Pang, Da Li, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
2018	J	`jnl`	Deep Factorised Inverse-Sketching. CoRR Kaiyue Pang, Da Li, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
2018	A*	`conf`	Learning to Generalize: Meta-Learning for Domain Generalization. AAAI Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales
2018	A*	`conf`	Sketch-a-Classifier: Sketch-Based Photo Classifier Generation. CVPR Conghui Hu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
2018	J	`jnl`	Sketch-a-Classifier: Sketch-based Photo Classifier Generation. CoRR Conghui Hu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
2017	A*	`conf`	Deeper, Broader and Artier Domain Generalization. ICCV Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales
2017	J	`jnl`	Deeper, Broader and Artier Domain Generalization. CoRR Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales
2017	J	`jnl`	Learning to Generalize: Meta-Learning for Domain Generalization. CoRR Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales
2017	A	`conf`	Now You See Me: Deep Face Hallucination for Unviewed Sketches. BMVC Conghui Hu, Da Li, Yi-Zhe Song, Timothy M. Hospedales