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How robust are pre-trained models to distribution shift?


Jun 17, 2022
Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal

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Adversarial Masking for Self-Supervised Learning


Jan 31, 2022
Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek

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Learning Multimodal VAEs through Mutual Supervision


Jul 01, 2021
Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, N. Siddharth

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Gradient Matching for Domain Generalization


Apr 20, 2021
Yuge Shi, Jeffrey Seely, Philip H. S. Torr, N. Siddharth, Awni Hannun, Nicolas Usunier, Gabriel Synnaeve

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Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models


Jul 02, 2020
Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth

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Action Anticipation with RBF Kernelized Feature Mapping RNN


Nov 19, 2019
Yuge Shi, Basura Fernando, Richard Hartley

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* Accepted for publication in ECCV2018 

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Action Anticipation with RBF KernelizedFeature Mapping RNN


Nov 18, 2019
Yuge Shi, Basura Fernando, Richard Hartley

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* Accepted for publication in ECCV2018 

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Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models


Nov 08, 2019
Yuge Shi, N. Siddharth, Brooks Paige, Philip H. S. Torr

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