Tree-Cut for Probabilistic Image Segmentation. - Shell Xu Hu; Christopher K. I. Williams; Sinisa Todorovic (CoRR, 2015)

Exploring Weight Symmetry in Deep Neural Network. - Shell Xu Hu; Sergey Zagoruyko; Nikos Komodakis (CoRR, 2018)

Variational Information Distillation for Knowledge Transfer. - Sungsoo Ahn; Shell Xu Hu; Andreas C. Damianou; Neil D. Lawrence; Zhenwen Dai (CVPR, 2019)

Exploring weight symmetry in deep neural networks. - Shell Xu Hu; Sergey Zagoruyko; Nikos Komodakis (Comput. Vis. Image Underst., 2019)

Empirical Bayes Transductive Meta-Learning with Synthetic Gradients. - Shell Xu Hu; Pablo Garcia Moreno; Yang Xiao 009; Xi Shen 001; Guillaume Obozinski; Neil D. Lawrence; Andreas C. Damianou (ICLR, 2020)

Boosting Co-Teaching With Compression Regularization for Label Noise. - Yingyi Chen; Xi Shen 001; Shell Xu Hu; Johan A. K. Suykens (CVPR Workshops, 2021)

AvaTr: One-Shot Speaker Extraction with Transformers. - Shell Xu Hu; Md Rifat Arefin; Viet-Nhat Nguyen; Alish Dipani; Xaq Pitkow; Andreas Savas Tolias (Interspeech, 2021)

Re-ranking for image retrieval and transductive few-shot classification. - Xi Shen 001; Yang Xiao 009; Shell Xu Hu; Othman Sbai; Mathieu Aubry (NeurIPS, 2021)

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)

Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut. - Yangtao Wang; Xi Shen 001; Shell Xu Hu; Yuan Yuan 002; James L. Crowley; Dominique Vaufreydaz (CVPR, 2022)

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

Feed-Forward Source-Free Latent Domain Adaptation via Cross-Attention. - Ondrej Bohdal; Da Li 001; Shell Xu Hu; 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)

Learning Where and When to Reason in Neuro-Symbolic Inference. - Cristina Cornelio; Jan Stühmer; Shell Xu Hu; Timothy M. Hospedales (NeSy, 2023)

Augmenting CLIP with Improved Visio-Linguistic Reasoning. - Samyadeep Basu; Maziar Sanjabi; Daniela Massiceti; Shell Xu Hu; Soheil Feizi (CoRR, 2023)

EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods. - Samyadeep Basu; Mehrdad Saberi; Shweta Bhardwaj; Atoosa Malemir Chegini; Daniela Massiceti; Maziar Sanjabi; Shell Xu Hu; Soheil Feizi (CoRR, 2023)

TokenCut: Segmenting Objects in Images and Videos With Self-Supervised Transformer and Normalized Cut. - Yangtao Wang; Xi Shen 001; Yuan Yuan 002; Yuming Du; Maomao Li; Shell Xu Hu; James L. Crowley; Dominique Vaufreydaz (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Strong Baselines for Parameter-Efficient Few-Shot Fine-Tuning. - Samyadeep Basu; Shell Xu Hu; Daniela Massiceti; Soheil Feizi (AAAI, 2024)

Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP. - Samyadeep Basu; Shell Xu Hu; Maziar Sanjabi; Daniela Massiceti; Soheil Feizi (EMNLP, 2024)

MobileQuant: Mobile-friendly Quantization for On-device Language Models. - Fuwen Tan; Royson Lee; Lukasz Dudziak; Shell Xu Hu; Sourav Bhattacharya; Timothy M. Hospedales; Georgios Tzimiropoulos; Brais Martínez (EMNLP (Findings), 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)

CLUES: Collaborative Private-domain High-quality Data Selection for LLMs via Training Dynamics. - Wanru Zhao; Hongxiang Fan; Shell Xu Hu; Wangchunshu Zhou; Nicholas D. Lane (NeurIPS, 2024)

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

BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science. - Xinna Lin; Siqi Ma; Junjie Shan; Xiaojing Zhang; Shell Xu Hu; Tiannan Guo; Stan Z. Li; Kaicheng Yu (CoRR, 2024)

Compressing Features for Learning With Noisy Labels. - Yingyi Chen; Shell Xu Hu; Xi Shen 001; Chunrong Ai; Johan A. K. Suykens (IEEE Trans. Neural Networks Learn. Syst., 2024)

FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization. - Hao Mark Chen; Shell Xu Hu; Wayne Luk; Timothy M. Hospedales; Hongxiang Fan (CoRR, 2025)

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization. - Zhican Wang; Guanghui He; Dantong Liu; Lingjun Gao; Shell Xu Hu; Chen Zhang; Zhuoran Song; Nicholas D. Lane; Wayne Luk; Hongxiang Fan (CoRR, 2025)

CLUES: Collaborative High-Quality Data Selection for LLMs via Training Dynamics. - Wanru Zhao; Hongxiang Fan; Shell Xu Hu; Wangchunshu Zhou; Bofan Chen; Nicholas D. Lane (CoRR, 2025)