Structure Inference for Bayesian Multisensory Perception and Tracking. - Timothy M. Hospedales; Joel J. Cartwright; Sethu Vijayakumar (IJCAI, 2007)

An Adaptive Machine Director. - Timothy M. Hospedales; Oliver Williams (BMVC, 2008)

Implications of Noise and Neural Heterogeneity for Vestibulo-Ocular Reflex Fidelity. - Timothy M. Hospedales; Mark C. W. van Rossum; Bruce P. Graham; Mayank B. Dutia (Neural Comput., 2008)

Structure Inference for Bayesian Multisensory Scene Understanding. - Timothy M. Hospedales; Sethu Vijayakumar (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Bayesian multisensory perception. - Timothy M. Hospedales (2008)

A Unified Bayesian Framework for Adaptive Visual Tracking. - Emanuel Zelniker; Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (BMVC, 2009)

A Markov Clustering Topic Model for mining behaviour in video. - Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (ICCV, 2009)

Learning Rare Behaviours. - Jian Li; Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (ACCV (2), 2010)

Learning Tags from Unsegmented Videos of Multiple Human Actions. - Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (ICDM, 2011)

Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning. - Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (PAKDD (2), 2011)

Identifying Rare and Subtle Behaviors: A Weakly Supervised Joint Topic Model. - Timothy M. Hospedales; Jian Li; Shaogang Gong; Tao Xiang 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Person Re-identification by Attributes. - Ryan Layne; Timothy M. Hospedales; Shaogang Gong (BMVC, 2012)

Stream-based joint exploration-exploitation active learning. - Chen Change Loy; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong (CVPR, 2012)

Attribute Learning for Understanding Unstructured Social Activity. - Yanwei Fu 001; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong (ECCV (4), 2012)

A Unifying Theory of Active Discovery and Learning. - Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (ECCV (5), 2012)

Towards Person Identification and Re-identification with Attributes. - Ryan Layne; Timothy M. Hospedales; Shaogang Gong (ECCV Workshops (1), 2012)

Video Behaviour Mining Using a Dynamic Topic Model. - Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (Int. J. Comput. Vis., 2012)

Bayesian Joint Topic Modelling for Weakly Supervised Object Localisation. - Zhiyuan Shi 001; Timothy M. Hospedales; Tao Xiang 002 (ICCV, 2013)

Domain transfer for person re-identification. - Ryan Layne; Timothy M. Hospedales; Shaogang Gong (ARTEMIS@ACM Multimedia, 2013)

Cross-domain traffic scene understanding by motion model transfer. - Xun Xu 002; Shaogang Gong; Timothy M. Hospedales (ARTEMIS@ACM Multimedia, 2013)

Finding Rare Classes: Active Learning with Generative and Discriminative Models. - Timothy M. Hospedales; Shaogang Gong; Tao Xiang 002 (IEEE Trans. Knowl. Data Eng., 2013)

Cross-Modal Face Matching: Beyond Viewed Sketches. - Shuxin Ouyang; Timothy M. Hospedales; Yi-Zhe Song; Xueming Li (ACCV (2), 2014)

Open-world Person Re-Identification by Multi-Label Assignment Inference. - Brais Cancela; Timothy M. Hospedales; Shaogang Gong (BMVC, 2014)

Transductive Multi-label Zero-shot Learning. - Yanwei Fu 001; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong (BMVC, 2014)

Re-id: Hunting Attributes in the Wild. - Ryan Layne; Timothy M. Hospedales; Shaogang Gong (BMVC, 2014)

Intra-category sketch-based image retrieval by matching deformable part models. - Yi Li 004; Timothy M. Hospedales; Yi-Zhe Song; Shaogang Gong (BMVC, 2014)

Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation. - Yanwei Fu 001; Timothy M. Hospedales; Tao Xiang 002; Zhen-Yong Fu; Shaogang Gong (ECCV (2), 2014)

Interestingness Prediction by Robust Learning to Rank. - Yanwei Fu 001; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong; Yuan Yao 011 (ECCV (2), 2014)

Investigating Open-World Person Re-identification Using a Drone. - Ryan Layne; Timothy M. Hospedales; Shaogang Gong (ECCV Workshops (3), 2014)

Weakly Supervised Learning of Objects, Attributes and Their Associations. - Zhiyuan Shi 001; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (ECCV (2), 2014)

A Survey on Heterogeneous Face Recognition: Sketch, Infra-red, 3D and Low-resolution. - Shuxin Ouyang; Timothy M. Hospedales; Yi-Zhe Song; Xueming Li (CoRR, 2014)

Learning Multimodal Latent Attributes. - Yanwei Fu 001; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

The Re-identification Challenge. - Shaogang Gong; Marco Cristani; Chen Change Loy; Timothy M. Hospedales (Person Re-Identification, 2014)

Attributes-Based Re-identification. - Ryan Layne; Timothy M. Hospedales; Shaogang Gong (Person Re-Identification, 2014)

Sketch-a-Net that Beats Humans. - Qian Yu; Yongxin Yang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (BMVC, 2015)

Making better use of edges via perceptual grouping. - Yonggang Qi; Yi-Zhe Song; Tao Xiang 002; Honggang Zhang 002; Timothy M. Hospedales; Yi Li 004; Jun Guo 002 (CVPR, 2015)

Transferring a semantic representation for person re-identification and search. - Zhiyuan Shi 001; Timothy M. Hospedales; Tao Xiang 002 (CVPR, 2015)

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 J. Christmas; Stan Z. Li; Timothy M. Hospedales (ICCV Workshops, 2015)

Semantic embedding space for zero-shot action recognition. - Xun Xu 002; Timothy M. Hospedales; Shaogang Gong (ICIP, 2015)

Probabilistic Graphical Models Parameter Learning with Transferred Prior and Constraints. - Yun Zhou 001; Norman E. Fenton; Timothy M. Hospedales; Martin Neil (UAI, 2015)

Transductive Multi-class and Multi-label Zero-shot Learning. - Yanwei Fu 001; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong (CoRR, 2015)

Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization. - Xun Xu 002; Timothy M. Hospedales; Shaogang Gong (CoRR, 2015)

Zero-Shot Action Recognition by Word-Vector Embedding. - Xun Xu 002; Timothy M. Hospedales; Shaogang Gong (CoRR, 2015)

A Unified Perspective on Multi-Domain and Multi-Task Learning. - Yongxin Yang; Timothy M. Hospedales (ICLR (Poster), 2015)

Deep Neural Networks for Sketch Recognition. - Yongxin Yang; Timothy M. Hospedales (CoRR, 2015)

Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian. - Yongxin Yang; Timothy M. Hospedales (CoRR, 2015)

Free-hand sketch recognition by multi-kernel feature learning. - Yi Li 004; Timothy M. Hospedales; Yi-Zhe Song; Shaogang Gong (Comput. Vis. Image Underst., 2015)

Transductive Multi-View Zero-Shot Learning. - Yanwei Fu 001; Timothy M. Hospedales; Tao Xiang 002; Shaogang Gong (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Bayesian Joint Modelling for Object Localisation in Weakly Labelled Images. - Zhiyuan Shi 001; Timothy M. Hospedales; Tao Xiang 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

L1 Graph Based Sparse Model for Label De-noising. - Xiaobin Chang; Tao Xiang 002; Timothy M. Hospedales (BMVC, 2016)

Deep Multi-task Attribute-driven Ranking for Fine-grained Sketch-based Image Retrieval. - Jifei Song; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales; Xiang Ruan (BMVC, 2016)

ForgetMeNot: Memory-Aware Forensic Facial Sketch Matching. - Shuxin Ouyang; Timothy M. Hospedales; Yi-Zhe Song; Xueming Li (CVPR, 2016)

Multivariate Regression on the Grassmannian for Predicting Novel Domains. - Yongxin Yang; Timothy M. Hospedales (CVPR, 2016)

Sketch Me That Shoe. - Qian Yu; Feng Liu 036; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales; Chen Change Loy (CVPR, 2016)

Multi-Task Zero-Shot Action Recognition with Prioritised Data Augmentation. - Xun Xu 002; Timothy M. Hospedales; Shaogang Gong (ECCV (2), 2016)

Towards Bottom-Up Analysis of Social Food. - Jaclyn Rich; Hamed Haddadi; Timothy M. Hospedales (Digital Health, 2016)

Gaussian Visual-Linguistic Embedding for Zero-Shot Recognition. - Tanmoy Mukherjee; Timothy M. Hospedales (EMNLP, 2016)

Emerging Topics in Learning from Noisy and Missing Data. - Xavier Alameda-Pineda; Timothy M. Hospedales; Elisa Ricci 001; Nicu Sebe; Xiaogang Wang 001 (ACM Multimedia, 2016)

Fine-grained sketch-based image retrieval: The role of part-aware attributes. - Ke Li 004; Kaiyue Pang; Yi-Zhe Song; Timothy M. Hospedales; Honggang Zhang 002; Yichuan Hu (WACV, 2016)

Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives. - Yongxin Yang; Timothy M. Hospedales (CoRR, 2016)

When and where to transfer for Bayesian network parameter learning. - Yun Zhou 001; Timothy M. Hospedales; Norman E. Fenton (Expert Syst. Appl., 2016)

A survey on heterogeneous face recognition: Sketch, infra-red, 3D and low-resolution. - Shuxin Ouyang; Timothy M. Hospedales; Yi-Zhe Song; Xueming Li; Chen Change Loy; Xiaogang Wang 001 (Image Vis. Comput., 2016)

Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels. - Yanwei Fu 001; Timothy M. Hospedales; Tao Xiang 002; Jiechao Xiong; Shaogang Gong; Yizhou Wang 001; Yuan Yao 011 (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Zero-Shot Crowd Behavior Recognition. - Xun Xu 002; Shaogang Gong; Timothy M. Hospedales (Group and Crowd Behavior for Computer Vision, 2017)

Gated Neural Networks for Option Pricing: Rationality by Design. - Yongxin Yang; Yu Zheng 032; Timothy M. Hospedales (AAAI, 2017)

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

Cross-domain Generative Learning for Fine-Grained Sketch-Based Image Retrieval. - Kaiyue Pang; Yi-Zhe Song; Tony Xiang; Timothy M. Hospedales (BMVC, 2017)

Fine-Grained Image Retrieval: the Text/Sketch Input Dilemma. - Jifei Song; Yi-Zhe Song; Tony Xiang; Timothy M. Hospedales (BMVC, 2017)

A Dataset for Persistent Multi-target Multi-camera Tracking in RGB-D. - Ryan Layne; Sion L. Hannuna; Massimo Camplani; Jake Hall; Timothy M. Hospedales; Tao Xiang 002; Majid Mirmehdi; Dima Damen (CVPR Workshops, 2017)

Semantic Regularisation for Recurrent Image Annotation. - Feng Liu 036; Tao Xiang 002; Timothy M. Hospedales; Wankou Yang; Changyin Sun 001 (CVPR, 2017)

Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks. - Guosheng Hu; Yang Hua 001; Yang Yuan; Zhihong Zhang 001; Zheng Lu; Sankha S. Mukherjee; Timothy M. Hospedales; Neil Martin Robertson; Yongxin Yang (ICCV, 2017)

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

Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval. - Jifei Song; Qian Yu; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (ICCV, 2017)

Transferring CNNS to multi-instance multi-label classification on small datasets. - Mingzhi Dong; Kunkun Pang; Yang Wu 001; Jing-Hao Xue; Timothy M. Hospedales; Tsukasa Ogasawara (ICIP, 2017)

Deep Multi-task Representation Learning: A Tensor Factorisation Approach. - Yongxin Yang; Timothy M. Hospedales (ICLR (Poster), 2017)

Trace Norm Regularised Deep Multi-Task Learning. - Yongxin Yang; Timothy M. Hospedales (ICLR (Workshop), 2017)

Tensor Based Knowledge Transfer Across Skill Categories for Robot Control. - Chenyang Zhao 007; Timothy M. Hospedales; Freek Stulp; Olivier Sigaud (IJCAI, 2017)

Deep Multi-View Learning with Stochastic Decorrelation Loss. - Xiaobin Chang; Tao Xiang 002; Timothy M. Hospedales (CoRR, 2017)

Learning to Learn: Meta-Critic Networks for Sample Efficient Learning. - Flood Sung; Li Zhang 040; Tao Xiang 002; Timothy M. Hospedales; Yongxin Yang (CoRR, 2017)

Actor-Critic Sequence Training for Image Captioning. - Li Zhang 040; Flood Sung; Feng Liu 036; Tao Xiang 002; Shaogang Gong; Yongxin Yang; Timothy M. Hospedales (CoRR, 2017)

Deep Matching Autoencoders. - Tanmoy Mukherjee; Makoto Yamada; Timothy M. Hospedales (CoRR, 2017)

The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching. - Qian Yu; Xiaobin Chang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (CoRR, 2017)

Free-Hand Sketch Synthesis with Deformable Stroke Models. - Yi Li 004; Yi-Zhe Song; Timothy M. Hospedales; Shaogang Gong (Int. J. Comput. Vis., 2017)

Transductive Zero-Shot Action Recognition by Word-Vector Embedding. - Xun Xu 002; Timothy M. Hospedales; Shaogang Gong (Int. J. Comput. Vis., 2017)

Sketch-a-Net: A Deep Neural Network that Beats Humans. - Qian Yu; Yongxin Yang; Feng Liu 036; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (Int. J. Comput. Vis., 2017)

Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes. - Zhiyuan Shi 001; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Discovery of Shared Semantic Spaces for Multiscene Video Query and Summarization. - Xun Xu 002; Timothy M. Hospedales; Shaogang Gong (IEEE Trans. Circuits Syst. Video Technol., 2017)

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval. - Ke Li 004; Kaiyue Pang; Yi-Zhe Song; Timothy M. Hospedales; Tao Xiang 002; Honggang Zhang 002 (IEEE Trans. Image Process., 2017)

Unifying Multi-domain Multitask Learning: Tensor and Neural Network Perspectives. - Yongxin Yang; Timothy M. Hospedales (Domain Adaptation in Computer Vision Applications, 2017)

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

SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval. - Peng Xu 005; Yongye Huang; Tongtong Yuan; Kaiyue Pang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales; Zhanyu Ma; Jun Guo 002 (CVPR, 2018)

Multi-Level Factorisation Net for Person Re-Identification. - Xiaobin Chang; Timothy M. Hospedales; Tao Xiang 002 (CVPR, 2018)

Scalable and Effective Deep CCA via Soft Decorrelation. - Xiaobin Chang; Tao Xiang 002; Timothy M. Hospedales (CVPR, 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)

IVQA: Inverse Visual Question Answering. - Feng Liu 036; Tao Xiang 002; Timothy M. Hospedales; Wankou Yang; Changyin Sun 001 (CVPR, 2018)

Learning Deep Sketch Abstraction. - Umar Riaz Muhammad; Yongxin Yang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (CVPR, 2018)

Learning to Sketch With Shortcut Cycle Consistency. - Jifei Song; Kaiyue Pang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (CVPR, 2018)

Learning to Compare: Relation Network for Few-Shot Learning. - Flood Sung; Yongxin Yang; Li Zhang 040; Tao Xiang 002; Philip H. S. Torr; Timothy M. Hospedales (CVPR, 2018)

Deep Mutual Learning. - Ying Zhang 021; Tao Xiang 002; Timothy M. Hospedales; Huchuan Lu (CVPR, 2018)

Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States. - Guosheng Hu; Li Liu 004; Yang Yuan; Zehao Yu; Yang Hua 001; Zhihong Zhang 001; Fumin Shen; Ling Shao 001; Timothy M. Hospedales; Neil Martin Robertson; Yongxin Yang (ECCV (12), 2018)

Universal Sketch Perceptual Grouping. - Ke Li 004; Kaiyue Pang; Jifei Song; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales; Honggang Zhang 002 (ECCV (8), 2018)

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

Learning Unsupervised Word Translations Without Adversaries. - Tanmoy Mukherjee; Makoto Yamada; Timothy M. Hospedales (EMNLP, 2018)

Deep Stock Representation Learning: From Candlestick Charts to Investment Decisions. - Guosheng Hu; Yuxin Hu; Kai Yang 031; Zehao Yu; Flood Sung; Zhihong Zhang 001; Fei Xie; Jianguo Liu; Neil Martin Robertson; Timothy M. Hospedales; Qiangwei Miemie (ICASSP, 2018)

Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice. - Kunkun Pang; Mingzhi Dong; Yang Wu 001; Timothy M. Hospedales (ICPR, 2018)

Visual Articulated Tracking in the Presence of Occlusions. - Christian Rauch 002; Timothy M. Hospedales; Jamie Shotton; Maurice F. Fallon (ICRA, 2018)

IEEE Access Special Section Editorial: Recent Advantages of Computer Vision. - Zhanyu Ma; Haibin Ling; Yi-Zhe Song; Timothy M. Hospedales; Wei Jia 001; Yuxin Peng; Aili Han (IEEE Access, 2018)

Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning. - Kunkun Pang; Mingzhi Dong; Yang Wu 001; Timothy M. Hospedales (CoRR, 2018)

Deep Neural Decision Trees. - Yongxin Yang; Irene Garcia Morillo; Timothy M. Hospedales (CoRR, 2018)

Universal Perceptual Grouping. - Ke Li 004; Kaiyue Pang; Jifei Song; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales; Honggang Zhang 002 (CoRR, 2018)

Generative Adversarial Policy Networks for Behavioural Repertoire. - Marija Jegorova; Stéphane Doncieux; Timothy M. Hospedales (CoRR, 2018)

Deep Comparison: Relation Columns for Few-Shot Learning. - Xueting Zhang; Flood Sung; Yuting Qiang; Yongxin Yang; Timothy M. Hospedales (CoRR, 2018)

Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. - Stéphane Doncieux; David Filliat; Natalia Díaz Rodríguez; Timothy M. Hospedales; Richard J. Duro; Alexandre Coninx; Diederik M. Roijers; Benoît Girard 001; Nicolas Perrin 001; Olivier Sigaud (Frontiers Neurorobotics, 2018)

Frankenstein: Learning Deep Face Representations Using Small Data. - Guosheng Hu; Xiaojiang Peng; Yongxin Yang; Timothy M. Hospedales; Jakob Verbeek (IEEE Trans. Image Process., 2018)

Disjoint Label Space Transfer Learning with Common Factorised Space. - Xiaobin Chang; Yongxin Yang; Tao Xiang 002; Timothy M. Hospedales (AAAI, 2019)

Frustratingly Easy Person Re-Identification: Generalizing Person Re-ID in Practice. - Jieru Jia; Qiuqi Ruan; Timothy M. Hospedales (BMVC, 2019)

Generalising Fine-Grained Sketch-Based Image Retrieval. - Kaiyue Pang; Ke Li 004; Yongxin Yang; Honggang Zhang 002; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (CVPR, 2019)

Generalizable Person Re-Identification by Domain-Invariant Mapping Network. - Jifei Song; Yongxin Yang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (CVPR, 2019)

TuckER: Tensor Factorization for Knowledge Graph Completion. - Ivana Balazevic; Carl Allen; Timothy M. Hospedales (EMNLP/IJCNLP (1), 2019)

Hypernetwork Knowledge Graph Embeddings. - Ivana Balazevic; Carl Allen; Timothy M. Hospedales (ICANN (Workshop), 2019)

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

Goal-Driven Sequential Data Abstraction. - Umar Riaz Muhammad; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (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)

Modelling the Single Word to Multi-Word Transition Using Matrix Completion. - Gabriella Pizzuto; Timothy M. Hospedales; Olga Capirci; Angelo Cangelosi (ICDL-EPIROB, 2019)

Analogies Explained: Towards Understanding Word Embeddings. - Carl Allen; Timothy M. Hospedales (ICML, 2019)

Feature-Critic Networks for Heterogeneous Domain Generalization. - Yiying Li; Yongxin Yang; Wei Zhou; Timothy M. Hospedales (ICML, 2019)

Learning-driven Coarse-to-Fine Articulated Robot Tracking. - Christian Rauch 002; Vladimir Ivan; Timothy M. Hospedales; Jamie Shotton; Maurice F. Fallon (ICRA, 2019)

What the Vec? Towards Probabilistically Grounded Embeddings. - Carl Allen; Ivana Balazevic; Timothy M. Hospedales (NeurIPS, 2019)

Multi-relational Poincaré Graph Embeddings. - Ivana Balazevic; Carl Allen; Timothy M. Hospedales (NeurIPS, 2019)

Investigating Generalisation in Continuous Deep Reinforcement Learning. - Chenyang Zhao 007; Olivier Sigaud; Freek Stulp; Timothy M. Hospedales (CoRR, 2019)

Physics-as-Inverse-Graphics: Joint Unsupervised Learning of Objects and Physics from Video. - Miguel Jaques; Michael Burke; Timothy M. Hospedales (CoRR, 2019)

Measuring the Transferability of Adversarial Examples. - Deyan Petrov; Timothy M. Hospedales (CoRR, 2019)

Zero-Shot Crowd Behavior Recognition. - Xun Xu 002; Shaogang Gong; Timothy M. Hospedales (CoRR, 2019)

On Understanding Knowledge Graph Representation. - Carl Allen; Ivana Balazevic; Timothy M. Hospedales (CoRR, 2019)

Deep clustering with concrete k-means. - Boyan Gao; Yongxin Yang; Henry Gouk; Timothy M. Hospedales (CoRR, 2019)

Toward Deep Universal Sketch Perceptual Grouper. - Ke Li 004; Kaiyue Pang; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales; Honggang Zhang 002 (IEEE Trans. Image Process., 2019)

Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach. - Yu Zheng 032; Bowei Chen 001; Timothy M. Hospedales; Yongxin Yang (AAAI, 2020)

Deep Domain-Adversarial Image Generation for Domain Generalisation. - Kaiyang Zhou; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (AAAI, 2020)

ALBA: Reinforcement Learning for Video Object Segmentation. - Shreyank N. Gowda; Panagiotis Eustratiadis; Timothy M. Hospedales; Laura Sevilla-Lara (BMVC, 2020)

Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval. - Ayan Kumar Bhunia; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (CVPR, 2020)

Unsupervised Batch Normalization. - Mustafa Taha Koçyigit; Laura Sevilla-Lara; Timothy M. Hospedales; Hakan Bilen (CVPR Workshops, 2020)

Factorized Higher-Order CNNs With an Application to Spatio-Temporal Emotion Estimation. - Jean Kossaifi; Antoine Toisoul; Adrian Bulat; Yannis Panagakis; Timothy M. Hospedales; Maja Pantic (CVPR, 2020)

Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval. - Kaiyue Pang; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (CVPR, 2020)

Incremental Few-Shot Object Detection. - Juan-Manuel Pérez-Rúa; Xiatian Zhu; Timothy M. Hospedales; Tao Xiang 002 (CVPR, 2020)

BézierSketch: A Generative Model for Scalable Vector Sketches. - Ayan Das 003; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (ECCV (26), 2020)

Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification. - Xiao Gong; Guosheng Hu; Timothy M. Hospedales; Yongxin Yang (ECCV Workshops (1), 2020)

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

Differentiable Automatic Data Augmentation. - Yonggang Li; Guosheng Hu; Yongtao Wang; Timothy M. Hospedales; Neil Martin Robertson; Yongxin Yang (ECCV (22), 2020)

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

Learning to Generate Novel Domains for Domain Generalization. - Kaiyang Zhou; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002 (ECCV (16), 2020)

Index tracking with differentiate asset selection. - Yu Zheng 032; Yunpeng Li 004; Qiuhua Xu; Timothy M. Hospedales; Yongxin Yang (ICAIF, 2020)

Deep Clustering for Domain Adaptation. - Boyan Gao; Yongxin Yang; Henry Gouk; Timothy M. Hospedales (ICASSP, 2020)

Deep Clusteringwith Concrete K-Means. - Boyan Gao; Yongxin Yang; Henry Gouk; Timothy M. Hospedales (ICASSP, 2020)

Diversity and Sparsity: A New Perspective on Index Tracking. - Yu Zheng 032; Timothy M. Hospedales; Yongxin Yang (ICASSP, 2020)

Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video. - Miguel Jaques; Michael Burke; Timothy M. Hospedales (ICLR, 2020)

Full-Scale Continuous Synthetic Sonar Data Generation with Markov Conditional Generative Adversarial Networks*. - Marija Jegorova; Antti Ilari Karjalainen; Jose Vazquez; Timothy M. Hospedales (ICRA, 2020)

RelationNet2: Deep Comparison Network for Few-Shot Learning. - Xueting Zhang; Yuting Qiang; Flood Sung; Yongxin Yang; Timothy M. Hospedales (IJCNN, 2020)

Adversarial Generation of Informative Trajectories for Dynamics System Identification. - Marija Jegorova; Joshua Smith 002; Michael N. Mistry; Timothy M. Hospedales (IROS, 2020)

Online Meta-Critic Learning for Off-Policy Actor-Critic Methods. - Wei Zhou; Yiying Li; Yongxin Yang; Huaimin Wang; Timothy M. Hospedales (NeurIPS, 2020)

Unlimited Resolution Image Generation with R2D2-GANs. - Marija Jegorova; Antti Ilari Karjalainen; Jose Vazquez; Timothy M. Hospedales (CoRR, 2020)

DADA: Differentiable Automatic Data Augmentation. - Yonggang Li; Guosheng Hu; Yongtao Wang; Timothy M. Hospedales; Neil Martin Robertson; Yongxing Yang (CoRR, 2020)

SimpleMKKM: Simple Multiple Kernel K-means. - Xinwang Liu 002; En Zhu; Jiyuan Liu 003; Timothy M. Hospedales; Yang Wang 023; Meng Wang 001 (CoRR, 2020)

DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics. - Stéphane Doncieux; Nicolas Bredèche; Leni K. Le Goff; Benoît Girard 001; Alexandre Coninx; Olivier Sigaud; Mehdi Khamassi; Natalia Díaz Rodríguez; David Filliat; Timothy M. Hospedales; A. E. Eiben; Richard J. Duro (CoRR, 2020)

Latent Domain Learning with Dynamic Residual Adapters. - Lucas Deecke; Timothy M. Hospedales; Hakan Bilen (CoRR, 2020)

A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning. - Carl Allen; Ivana Balazevic; Timothy M. Hospedales (CoRR, 2020)

Flexible Dataset Distillation: Learn Labels Instead of Images. - Ondrej Bohdal; Yongxin Yang; Timothy M. Hospedales (CoRR, 2020)

Don't Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights. - Linus Ericsson; Henry Gouk; Timothy M. Hospedales (CoRR, 2020)

Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows. - Ivana Balazevic; Carl Allen; Timothy M. Hospedales (CoRR, 2020)

On Learning Semantic Representations for Million-Scale Free-Hand Sketches. - Peng Xu 005; Yongye Huang; Tongtong Yuan; Tao Xiang 002; Timothy M. Hospedales; Yi-Zhe Song; Liang Wang 001 (CoRR, 2020)

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

Margin-Based Transfer Bounds for Meta Learning with Deep Feature Embedding. - Jiechao Guan; Zhiwu Lu 001; Tao Xiang 002; Timothy M. Hospedales (CoRR, 2020)

Editorial: Special Issue on Machine Vision with Deep Learning. - Ling Shao 001; Hubert P. H. Shum; Timothy M. Hospedales (Int. J. Comput. Vis., 2020)

Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool. - Feng Liu 036; Tao Xiang 002; Timothy M. Hospedales; Wankou Yang; Changyin Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 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)

Deep Ranking for Image Zero-Shot Multi-Label Classification. - Zhong Ji; Biying Cui; Huihui Li; Yu-Gang Jiang 001; Tao Xiang 002; Timothy M. Hospedales; Yanwei Fu 001 (IEEE Trans. Image Process., 2020)

Pixelor: a competitive sketching AI agent. so you think you can sketch? - Ayan Kumar Bhunia; Ayan Das 003; Umar Riaz Muhammad; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yulia Gryaditskaya; Yi-Zhe Song (ACM Trans. Graph., 2020)

Neural-Symbolic Integration: A Compositional Perspective. - Efthymia Tsamoura; Timothy M. Hospedales; Loizos Michael (AAAI, 2021)

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

Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation. - Chenyang Zhao 007; Timothy M. Hospedales (ACML, 2021)

Defensive Tensorization. - Adrian Bulat; Jean Kossaifi; Sourav Bhattacharya; Yannis Panagakis; Timothy M. Hospedales; Georgios Tzimiropoulos; Nicholas D. Lane; Maja Pantic (BMVC, 2021)

Tensor Composition Net for Visual Relationship Prediction. - Yuting Qiang; Yongxin Yang; Xueting Zhang; Yanwen Guo 001; Timothy M. Hospedales (BMVC, 2021)

Cloud2Curve: Generation and Vectorization of Parametric Sketches. - Ayan Das 003; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (CVPR, 2021)

Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. - Ayan Kumar Bhunia; Pinaki Nath Chowdhury; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (CVPR, 2021)

How Well Do Self-Supervised Models Transfer? - Linus Ericsson; Henry Gouk; Timothy M. Hospedales (CVPR, 2021)

NewtonianVAE: Proportional Control and Goal Identification From Pixels via Physical Latent Spaces. - Miguel Jaques; Michael Burke; Timothy M. Hospedales (CVPR, 2021)

Searching for Robustness: Loss Learning for Noisy Classification Tasks. - Boyan Gao; Henry Gouk; Timothy M. Hospedales (ICCV, 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)

Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. - Xueting Zhang; Debin Meng; Henry Gouk; Timothy M. Hospedales (ICCV, 2021)

Interpreting Knowledge Graph Relation Representation from Word Embeddings. - Carl Allen; Ivana Balazevic; Timothy M. Hospedales (ICLR, 2021)

Distance-Based Regularisation of Deep Networks for Fine-Tuning. - Henry Gouk; Timothy M. Hospedales; Massimiliano Pontil (ICLR, 2021)

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

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. - Adrian El Baz; Ihsan Ullah; Edesio Alcobaça; André C. P. L. F. de Carvalho; Hong Chen 011; Fabio Ferreira; Henry Gouk; Chaoyu Guan; Isabelle Guyon; Timothy M. Hospedales; Shell Hu; Mike Huisman; et al. (NeurIPS (Competition and Demos), 2021)

EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. - Ondrej Bohdal; Yongxin Yang; Timothy M. Hospedales (NeurIPS, 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)

FedH2L: Federated Learning with Model and Statistical Heterogeneity. - Yiying Li; Wei Zhou; Huaimin Wang; Haibo Mi; Timothy M. Hospedales (CoRR, 2021)

Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error. - Ondrej Bohdal; Yongxin Yang; Timothy M. Hospedales (CoRR, 2021)

Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation. - Minyoung Kim 001; Timothy M. Hospedales (CoRR, 2021)

Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks. - Linus Ericsson; Henry Gouk; Timothy M. Hospedales (CoRR, 2021)

Fine-Grained Instance-Level Sketch-Based Image Retrieval. - Qian Yu; Jifei Song; Yi-Zhe Song; Tao Xiang 002; Timothy M. Hospedales (Int. J. Comput. Vis., 2021)

On Learning Semantic Representations for Large-Scale Abstract Sketches. - Peng Xu 005; Yongye Huang; Tongtong Yuan; Tao Xiang 002; Timothy M. Hospedales; Yi-Zhe Song; Liang Wang 001 (IEEE Trans. Circuits Syst. Video Technol., 2021)

Fine-Grained Instance-Level Sketch-Based Video Retrieval. - Peng Xu 005; Kun Liu 016; Tao Xiang 002; Timothy M. Hospedales; Zhanyu Ma; Jun Guo 002; Yi-Zhe Song (IEEE Trans. Circuits Syst. Video Technol., 2021)

Toward Fine-Grained Sketch-Based 3D Shape Retrieval. - Anran Qi; Yulia Gryaditskaya; Jifei Song; Yongxin Yang; Yonggang Qi; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (IEEE Trans. Image Process., 2021)

Why Do Self-Supervised Models Transfer? On the Impact of Invariance on Downstream Tasks. - Linus Ericsson; Henry Gouk; Timothy M. Hospedales (BMVC, 2022)

Towards Unsupervised Sketch-based Image Retrieval. - Conghui Hu; Yongxin Yang; Yunpeng Li 004; Timothy M. Hospedales; 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)

MetaAudio: A Few-Shot Audio Classification Benchmark. - Calum Heggan; Sam Budgett; Timothy M. Hospedales; Mehrdad Yaghoobi (ICANN (1), 2022)

SketchODE: Learning neural sketch representation in continuous time. - Ayan Das 003; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (ICLR, 2022)

Visual Representation Learning over Latent Domains. - Lucas Deecke; Timothy M. Hospedales; Hakan Bilen (ICLR, 2022)

Online Hyperparameter Meta-Learning with Hypergradient Distillation. - Haebeom Lee; Hayeon Lee; Jaewoong Shin; Eunho Yang; Timothy M. Hospedales; Sung Ju Hwang (ICLR, 2022)

Loss Function Learning for Domain Generalization by Implicit Gradient. - Boyan Gao; Henry Gouk; Yongxin Yang; Timothy M. Hospedales (ICML, 2022)

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

Vision-based System Identification and 3D Keypoint Discovery using Dynamics Constraints. - Miguel Jaques; Martin Asenov; Michael Burke; Timothy M. Hospedales (L4DC, 2022)

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

Meta Mirror Descent: Optimiser Learning for Fast Convergence. - Boyan Gao; Henry Gouk; Haebeom Lee; 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)

HyperInvariances: Amortizing Invariance Learning. - Ruchika Chavhan; Henry Gouk; Jan Stühmer; Timothy M. Hospedales (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)

Meta-Learning in Neural Networks: A Survey. - Timothy M. Hospedales; Antreas Antoniou; Paul Micaelli; Amos J. Storkey (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Self-Supervised Representation Learning: Introduction, advances, and challenges. - Linus Ericsson; Henry Gouk; Chen Change Loy; Timothy M. Hospedales (IEEE Signal Process. Mag., 2022)

Behavioral Repertoire via Generative Adversarial Policy Networks. - Marija Jegorova; Stéphane Doncieux; Timothy M. Hospedales (IEEE Trans. Cogn. Dev. Syst., 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)

Partial Index Tracking: A Meta-Learning Approach. - Yongxin Yang; Timothy M. Hospedales (CoLLAs, 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)

An Erudite Fine-Grained Visual Classification Model. - Dongliang Chang; Yujun Tong; Ruoyi Du; Timothy M. Hospedales; Yi-Zhe Song; Zhanyu Ma (CVPR, 2023)

On-the-Fly Category Discovery. - Ruoyi Du; Dongliang Chang; Kongming Liang; Timothy M. Hospedales; Yi-Zhe Song; Zhanyu Ma (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)

An Evaluation of Self-supervised Learning for Portfolio Diversification. - Yongxin Yang; Timothy M. Hospedales (ICANN (3), 2023)

Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months. - Fady Rezk; Antreas Antoniou; Henry Gouk; Timothy M. Hospedales (ICBINB, 2023)

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

Task-aware Adaptive Learning for Cross-domain Few-shot Learning. - Yurong Guo; Ruoyi Du; Yuan Dong; Timothy M. Hospedales; Yi-Zhe Song; Zhanyu Ma (ICCV, 2023)

ChiroDiff: Modelling chirographic data with Diffusion Models. - Ayan Das 003; Yongxin Yang; Timothy M. Hospedales; Tao Xiang 002; Yi-Zhe Song (ICLR, 2023)

Amortised Invariance Learning for Contrastive Self-Supervision. - Ruchika Chavhan; Jan Stuehmer; Calum Heggan; Mehrdad Yaghoobi; Timothy M. Hospedales (ICLR, 2023)

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

MEDFAIR: Benchmarking Fairness for Medical Imaging. - Yongshuo Zong; Yongxin Yang; Timothy M. Hospedales (ICLR, 2023)

MT-SLVR: Multi-Task Self-Supervised Learning for Transformation In(Variant) Representations. - Calum Heggan; Timothy M. Hospedales; Sam Budgett; Mehrdad Yaghoobi (INTERSPEECH, 2023)

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

BayesTune: Bayesian Sparse Deep Model Fine-tuning. - Minyoung Kim 001; Timothy M. Hospedales (NeurIPS, 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)

On Calibration of Mathematical Finance Models by Hypernetworks. - Yongxin Yang; Timothy M. Hospedales (ECML/PKDD (6), 2023)

Mixture of Normalizing Flows for European Option Pricing. - Yongxin Yang; Timothy M. Hospedales (UAI, 2023)

Accelerating Self-Supervised Learning via Efficient Training Strategies. - Mustafa Taha Koçyigit; Timothy M. Hospedales; Hakan Bilen (WACV, 2023)

Amortised Invariance Learning for Contrastive Self-Supervision. - Ruchika Chavhan; Henry Gouk; Jan Stuehmer; Calum Heggan; Mehrdad Yaghoobi; Timothy M. Hospedales (CoRR, 2023)

Fairness meets Cross-Domain Learning: a new perspective on Models and Metrics. - Leonardo Iurada; Silvia Bucci; Timothy M. Hospedales; Tatiana Tommasi (CoRR, 2023)

Fairness in AI and Its Long-Term Implications on Society. - Ondrej Bohdal; Timothy M. Hospedales; Philip H. S. Torr; Fazl Barez (CoRR, 2023)

FedHB: Hierarchical Bayesian Federated Learning. - Minyoung Kim 001; Timothy M. Hospedales (CoRR, 2023)

A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning. - Minyoung Kim 001; Timothy M. Hospedales (CoRR, 2023)

Impact of Noise on Calibration and Generalisation of Neural Networks. - Martin Ferianc; Ondrej Bohdal; Timothy M. Hospedales; Miguel R. D. Rodrigues (CoRR, 2023)

Evaluating the Evaluators: Are Current Few-Shot Learning Benchmarks Fit for Purpose? - Luísa Shimabucoro; Timothy M. Hospedales; Henry Gouk (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)

BayesDLL: Bayesian Deep Learning Library. - Minyoung Kim 001; Timothy M. Hospedales (CoRR, 2023)

Deep Learning for Free-Hand Sketch: A Survey. - Peng Xu 005; Timothy M. Hospedales; Qiyue Yin; Yi-Zhe Song; Tao Xiang 002; Liang Wang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 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)

Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error. - Ondrej Bohdal; Yongxin Yang; Timothy M. Hospedales (Trans. Mach. Learn. Res., 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)

SketchINR: A First Look into Sketches as Implicit Neural Representations. - Hmrishav Bandyopadhyay; Ayan Kumar Bhunia; Pinaki Nath Chowdhury; Aneeshan Sain; Tao Xiang 002; Timothy M. Hospedales; Yi-Zhe Song (CVPR, 2024)

DemoFusion: Democratising High-Resolution Image Generation With No $$$. - Ruoyi Du; Dongliang Chang; Timothy M. Hospedales; Yi-Zhe Song; Zhanyu Ma (CVPR, 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)

On the Transferability of Large-Scale Self-Supervision to Few-Shot Audio Classification. - Calum Heggan; Sam Budgett; Timothy M. Hospedales; Mehrdad Yaghoobi (ICASSP Workshops, 2024)

FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis. - Raman Dutt; Ondrej Bohdal; Sotirios A. Tsaftaris; Timothy M. Hospedales (ICLR, 2024)

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

A Hierarchical Bayesian Model for Few-Shot Meta Learning. - Minyoung Kim 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)

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models. - Yongshuo Zong; Ondrej Bohdal; Tingyang Yu; Yongxin Yang; Timothy M. Hospedales (ICML, 2024)

Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations. - Yongshuo Zong; Tingyang Yu; Ruchika Chavhan; Bingchen Zhao; Timothy M. Hospedales (ICML, 2024)

From Pixels to Waveforms: Evaluating Pre-trained Image Models for Few-Shot Audio Classification. - Calum Heggan; Timothy M. Hospedales; Sam Budgett; Mehrdad Yaghoobi (IJCNN, 2024)

Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity. - Raman Dutt; Linus Ericsson; Pedro Sanchez; Sotirios A. Tsaftaris; Timothy M. Hospedales (MIDL, 2024)

A Bayesian Approach to Data Point Selection. - Xinnuo Xu; Minyoung Kim 001; Royson Lee; Brais Martínez; Timothy M. Hospedales (NeurIPS, 2024)

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

Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. - Royson Lee; Rui Li 052; Stylianos I. Venieris; Timothy M. Hospedales; Ferenc Huszár; Nicholas D. Lane (WACV, 2024)

Fairness Meets Cross-Domain Learning: A Benchmark of Models and Metrics. - Leonardo Iurada; Silvia Bucci; Timothy M. Hospedales; Tatiana Tommasi (IEEE Access, 2024)

VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning. - Yongshuo Zong; Ondrej Bohdal; Timothy M. Hospedales (CoRR, 2024)

MemControl: Mitigating Memorization in Medical Diffusion Models via Automated Parameter Selection. - Raman Dutt; Pedro Sanchez; Ondrej Bohdal; Sotirios A. Tsaftaris; Timothy M. Hospedales (CoRR, 2024)

Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning. - Bingchen Zhao; Yongshuo Zong; Letian Zhang; Timothy M. Hospedales (CoRR, 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)

Capacity Control is an Effective Memorization Mitigation Mechanism in Text-Conditional Diffusion Models. - Raman Dutt; Pedro Sanchez; Ondrej Bohdal; Sotirios A. Tsaftaris; Timothy M. Hospedales (CoRR, 2024)

Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks. - Martin Ferianc; Ondrej Bohdal; Timothy M. Hospedales; Miguel R. D. Rodrigues (Trans. Mach. Learn. Res., 2024)

Evaluating the Evaluators: Are Validation Methods for Few-Shot Learning Fit for Purpose? - Luísa Shimabucoro; Ruchika Chavhan; Timothy M. Hospedales; Henry Gouk (Trans. Mach. Learn. Res., 2024)

Editorial: Learning With Fewer Labels in Computer Vision. - Li Liu 002; Timothy M. Hospedales; Yann LeCun; Mingsheng Long; Jiebo Luo 001; Wanli Ouyang; Matti Pietikäinen; Tinne Tuytelaars (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning. - Minyoung Kim 001; Timothy M. Hospedales (AAAI, 2025)

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

LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning. - Minyoung Kim 001; Timothy M. Hospedales (ICLR, 2025)

VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning. - Yongshuo Zong; Ondrej Bohdal; Timothy M. Hospedales (ICLR, 2025)

MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter Selection. - Raman Dutt; Ondrej Bohdal; Pedro Sanchez; Sotirios A. Tsaftaris; Timothy M. Hospedales (WACV, 2025)

Enhancing Generalization via Sharpness-Aware Trajectory Matching for Dataset Condensation. - Boyan Gao; Bo Zhao; Shreyank N. Gowda; Xingrun Xing; Yibo Yang; Timothy M. Hospedales; David A. Clifton (CoRR, 2025)

FedP2EFT: Federated Learning to Personalize Parameter Efficient Fine-Tuning for Multilingual LLMs. - Royson Lee; Minyoung Kim 001; Fady Rezk; Rui Li 052; Stylianos I. Venieris; Timothy M. Hospedales (CoRR, 2025)

Model Diffusion for Certifiable Few-shot Transfer Learning. - Fady Rezk; Royson Lee; Henry Gouk; Timothy M. Hospedales; Minyoung Kim 001 (CoRR, 2025)

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

CheXGenBench: A Unified Benchmark For Fidelity, Privacy and Utility of Synthetic Chest Radiographs. - Raman Dutt; Pedro Sanchez; Yongchen Yao; Steven McDonagh 001; Sotirios A. Tsaftaris; Timothy M. Hospedales (CoRR, 2025)

Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning. - Taehoon Kim; Henry Gouk; Minyoung Kim 001; Timothy M. Hospedales (CoRR, 2025)

Self-Supervised Multimodal Learning: A Survey. - Yongshuo Zong; Oisin Mac Aodha; Timothy M. Hospedales (IEEE Trans. Pattern Anal. Mach. Intell., 2025)