Henry Gouk

Regularisation of neural networks by enforcing Lipschitz continuity pdf

Bernhard Pfahringer, Michael J. Cree, Eibe Frank, 2018, Machine Learning.

Accelerating Convolutional Neural Network Systems

Henry Gouk, Henry G. R. Gouk, H. Gouk, 2014 .

Searching for Robustness: Loss Learning for Noisy Classification Tasks

Timothy M. Hospedales, Timothy M. Hospedales, Henry Gouk, 2020, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification

F. Hutter, I. Guyon, Fábio Ferreira, 2022, NeurIPS.

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification

F. Hutter, I. Guyon, Fábio Ferreira, 2022, NeurIPS.

Why Do Self-Supervised Models Transfer? On the Impact of Invariance on Downstream Tasks

Timothy M. Hospedales, Henry Gouk, Linus Ericsson, 2021, BMVC.

Loss Function Learning for Domain Generalization by Implicit Gradient

Timothy M. Hospedales, Yongxin Yang, Henry Gouk, 2022, ICML.

Attacking Adversarial Defences by Smoothing the Loss Landscape

Timothy M. Hospedales, Da Li, Henry Gouk, 2022, ArXiv.

Weight-covariance alignment for adversarially robust neural networks

Timothy M. Hospedales, Da Li, Henry Gouk, 2020, ICML.