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Ruth Fong
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Cited by
Year
Interpretable explanations of black boxes by meaningful perturbation
RC Fong, A Vedaldi
IEEE International Conference on Computer Vision (ICCV), 2017
10482017
Understanding deep networks via extremal perturbations and smooth masks
R Fong, M Patrick, A Vedaldi
IEEE/CVF International Conference on Computer Vision (ICCV), 2950-2958, 2019
2112019
Net2vec: Quantifying and explaining how concepts are encoded by filters in deep neural networks
R Fong, A Vedaldi
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 8730-8738, 2018
1492018
Toward trustworthy AI development: mechanisms for supporting verifiable claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
1282020
Multi-modal self-supervision from generalized data transformations
M Patrick, YM Asano, P Kuznetsova, R Fong, JF Henriques, G Zweig, ...
arXiv preprint arXiv:2003.04298, 2020
922020
There and back again: Revisiting backpropagation saliency methods
SA Rebuffi, R Fong, X Ji, A Vedaldi
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8839-8848, 2020
642020
Using human brain activity to guide machine learning
RC Fong, WJ Scheirer, DD Cox
Scientific reports 8 (1), 1-10, 2018
592018
Explanations for attributing deep neural network predictions
R Fong, A Vedaldi
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 149-167, 2019
362019
On compositions of transformations in contrastive self-supervised learning
M Patrick, YM Asano, P Kuznetsova, R Fong, JF Henriques, G Zweig, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
122021
Contextual Semantic Interpretability
D Marcos, R Fong, S Lobry, R Flamary, N Courty, D Tuia
Asian Conference on Computer Vision (ACCV), 2020
112020
Occlusions for effective data augmentation in image classification
R Fong, A Vedaldi
IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) on …, 2019
112019
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning
I Laina, RC Fong, A Vedaldi
Neural Information Processing Systems (NeurIPS), 2020
42020
NormGrad: Finding the pixels that matter for training
SA Rebuffi, R Fong, X Ji, H Bilen, A Vedaldi
arXiv preprint arXiv:1910.08823, 2019
32019
HIVE: Evaluating the Human Interpretability of Visual Explanations
SSY Kim, N Meister, VV Ramaswamy, R Fong, O Russakovsky
arXiv preprint arXiv:2112.03184, 2021
22021
Debiasing Convolutional Neural Networks via Meta Orthogonalization
KE David, Q Liu, R Fong
Neural Information Processing Systems Workshop (NeurIPSW) on Algorithmic …, 2020
22020
Understanding convolutional neural networks
R Fong
University of Oxford, 2020
12020
On compositions of transformations in contrastive self-supervised learning
YM Asano, M Patrick, P Kuznetsova, R Fong, JF Henriques, G Zweig, ...
IEEE, 2022
2022
xxAI-Beyond Explainable Artificial Intelligence
A Holzinger, R Goebel, R Fong, T Moon, KR Müller, W Samek
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2022
2022
Interactive Similarity Overlays
R Fong, A Mordvintsev, A Vedaldi, C Olah
VISxAI, 2021
2021
Kuramoto Model Simulation
R Fong, J Russell, G Weerasinghe, R Bogacz
University of Oxford, 2018
2018
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