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On the Effectiveness of Compact Biomedical Transformers


Sep 07, 2022
Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki, David A. Clifton


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COPER: Continuous Patient State Perceiver


Aug 05, 2022
Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, David A. Clifton

* 2 figures; to present in IEEE International Conference on Biomedical and Health Informatics (IEEE BHI-2022) 

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Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling


Jul 24, 2022
Taha Ceritli, Andrew P. Creagh, David A. Clifton


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ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State


Jun 30, 2022
Xinshao Wang, Yang Hua, Elyor Kodirov, Sankha Subhra Mukherjee, David A. Clifton, Neil M. Robertson

* This work presents a new insightful finding to complement a previous one "deep neural networks easily fit random labels [99]": Deep models fit and generalise significantly less confident when more random labels exist. ProSelfLC redirects and promotes entropy minimisation, which is in marked contrast to recent practices of confidence penalty [16, 59, 72] 

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Multimodal Learning with Transformers: A Survey


Jun 13, 2022
Peng Xu, Xiatian Zhu, David A. Clifton


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Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data


Jun 06, 2022
Hang Yuan, Shing Chan, Andrew P. Creagh, Catherine Tong, David A. Clifton, Aiden Doherty


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Deep Reinforcement Learning for Multi-class Imbalanced Training


May 24, 2022
Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David A. Clifton


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How to Understand Masked Autoencoders


Feb 09, 2022
Shuhao Cao, Peng Xu, David A. Clifton


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Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning


Jul 04, 2021
Rasheed el-Bouri, Tingting Zhu, David A. Clifton

* 11 pages, 8 figures 

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Not All Knowledge Is Created Equal


Jun 02, 2021
Ziyun Li, Xinshao Wang, Haojin Yang, Di Hu, Neil M. Robertson, David A. Clifton, Christoph Meinel

* Selective mutual knowledge distillation 

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