10 citations · 10 across the 5 of their papers we have counts for
5 papers
CLEF: Clinically-Guided Contrastive Learning for Electrocardiogram Foundation Models
Yuxuan Shu, Peter H. Charlton, Fahim Kawsar +2
The electrocardiogram (ECG) is a key diagnostic tool in cardiovascular health. Single-lead ECG recording is integrated into both clinical-grade and consumer wearables. While self-s…
Sonnet: Spectral Operator Neural Network for Multivariable Time Series Forecasting
Yuxuan Shu, Vasileios Lampos
Multivariable time series forecasting methods can integrate information from exogenous variables, leading to significant prediction accuracy gains. The transformer architecture has…
DeformTime: Capturing Variable Dependencies with Deformable Attention for Time Series Forecasting
Yuxuan Shu, Vasileios Lampos
In multivariable time series (MTS) forecasting, existing state-of-the-art deep learning approaches tend to focus on autoregressive formulations and often overlook the potential of…
Unsupervised hard Negative Augmentation for contrastive learning
Yuxuan Shu, Vasileios Lampos
We present Unsupervised hard Negative Augmentation (UNA), a method that generates synthetic negative instances based on the term frequency-inverse document frequency (TF-IDF) retri…
Revisiting Self-Supervised Contrastive Learning for Facial Expression Recognition
Yuxuan Shu, Xiao Gu, Guang-Zhong Yang +1
The success of most advanced facial expression recognition works relies heavily on large-scale annotated datasets. However, it poses great challenges in acquiring clean and consist…