35 citations · 113 across the 10 of their papers we have counts for
13 papers
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
Peng Jin, Jinfa Huang, Fenglin Liu +5
Most video-and-language representation learning approaches employ contrastive learning, e.g., CLIP, to project the video and text features into a common latent space according to t…
On the Effectiveness of Compact Biomedical Transformers
Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki +1
Language models pre-trained on biomedical corpora, such as BioBERT, have recently shown promising results on downstream biomedical tasks. Many existing pre-trained models, on the o…
How to Understand Masked Autoencoders
Shuhao Cao, Peng Xu, David A. Clifton
"Masked Autoencoders (MAE) Are Scalable Vision Learners" revolutionizes the self-supervised learning method in that it not only achieves the state-of-the-art for image pre-training…
Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
Rasheed el-Bouri, Tingting Zhu, David A. Clifton
Given the abundance and ease of access of personal data today, individual privacy has become of paramount importance, particularly in the healthcare domain. In this work, we aim to…
Let Your Heart Speak in its Mother Tongue: Multilingual Captioning of Cardiac Signals
Dani Kiyasseh, Tingting Zhu, David Clifton
Cardiac signals, such as the electrocardiogram, convey a significant amount of information about the health status of a patient which is typically summarized by a clinician in the…
PCPs: Patient Cardiac Prototypes
Dani Kiyasseh, Tingting Zhu, David A. Clifton
Many clinical deep learning algorithms are population-based and difficult to interpret. Such properties limit their clinical utility as population-based findings may not generalize…