Fast Sliding Window Classification with Convolutional Neural Networks. - Henry G. R. Gouk; Anthony M. Blake (IVCNZ, 2014)

Learning Similarity Metrics by Factorising Adjacency Matrices. - Henry Gouk; Bernhard Pfahringer; Michael J. Cree (CoRR, 2015)

Learning Distance Metrics for Multi-Label Classification. - Henry Gouk; Bernhard Pfahringer; Michael J. Cree (ACML, 2016)

Estimating heading direction from monocular video sequences using biologically-based sensors. - Michael J. Cree; John A. Perrone; Gehan Anthonys; Aden C. Garnett; Henry Gouk (IVCNZ, 2016)

MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. - Henry Gouk; Bernhard Pfahringer; Eibe Frank; Michael J. Cree (ECML/PKDD (1), 2018)

Stochastic Gradient Trees. - Henry Gouk; Bernhard Pfahringer; Eibe Frank (ACML, 2019)

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

Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes. - Vithya Yogarajan; Henry Gouk; Tony Smith; Michael Mayo; Bernhard Pfahringer (ACIIDS (1), 2020)

A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning. - Hongyu Wang 008; Henry Gouk; Eibe Frank; Bernhard Pfahringer; Michael Mayo (Australasian Conference on Artificial Intelligence, 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)

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

Altruistic Decision-Making for Autonomous Driving with Sparse Rewards. - Jack Geary; Henry Gouk (CoRR, 2020)

Resolving Conflict in Decision-Making for Autonomous Driving. - Jack Geary; Henry Gouk (CoRR, 2020)

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

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

Searching for Robustness: Loss Learning for Noisy Classification Tasks. - Boyan Gao; Henry Gouk; 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)

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)

Resolving Conflict in Decision-Making for Autonomous Driving. - Jack Geary; Subramanian Ramamoorthy; Henry Gouk (Robotics: Science and Systems, 2021)

Active Altruism Learning and Information Sufficiency for Autonomous Driving. - Jack Geary; Henry Gouk; Subramanian Ramamoorthy (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)

Regularisation of neural networks by enforcing Lipschitz continuity. - Henry Gouk; Eibe Frank; Bernhard Pfahringer; Michael J. Cree (Mach. Learn., 2021)

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

Advances in Metalearning: ECML/PKDD Workshop on Meta-Knowledge Transfer. - Pavel Brazdil; Jan N. van Rijn; Henry Gouk; Felix Mohr (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract. - Hongyu Wang 008; Huon Fraser; Henry Gouk; Eibe Frank; Bernhard Pfahringer; Michael Mayo; Geoff Holmes 001 (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

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

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; André C. P. L. F. de Carvalho; Hong Chen 011; Fabio Ferreira; Henry Gouk; Shell Hu; Frank Hutter; Zhengying Liu; Felix Mohr; Jan N. van Rijn; Xin Wang 019; Isabelle Guyon (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)

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

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)

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)

Effectiveness of Debiasing Techniques: An Indigenous Qualitative Analysis. - Vithya Yogarajan; Gillian Dobbie; Henry Gouk (Tiny Papers @ ICLR, 2023)

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

Evaluating the Evaluators: Are Current Few-Shot Learning Benchmarks Fit for Purpose? - Luísa Shimabucoro; Timothy M. Hospedales; Henry Gouk (CoRR, 2023)

Skin Malignancy Classification Using Patients' Skin Images and Meta-data: Multimodal Fusion for Improving Fairness. - Ke Wang; Ningyuan Shan; Henry Gouk; Iris Szu-Szu Ho (MIDL, 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)

Strategic Classification with Randomised Classifiers. - Jack Geary; Henry Gouk (CoRR, 2025)

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

Is Limited Participant Diversity Impeding EEG-based Machine Learning? - Philipp Bomatter; Henry Gouk (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)