Fully-test-time adaptation (F-TTA) can mitigate performance loss due to
...
Preserving training dynamics across batch sizes is an important tool for...
The mechanisms behind the success of multi-view self-supervised learning...
Multiview Self-Supervised Learning (MSSL) is based on learning invarianc...
Training stability is of great importance to Transformers. In this work,...
Self-supervised representation learning (SSL) methods provide an effecti...
Transformers have gained increasing popularity in a wide range of
applic...
To achieve the promoted benefits of an AI symptom checker, laypeople mus...
While state-of-the-art contrastive Self-Supervised Learning (SSL) models...
In this work we examine how fine-tuning impacts the fairness of contrast...
Despite the success of a number of recent techniques for visual
self-sup...
The modelling of Electronic Health Records (EHRs) has the potential to d...
Medical Triage is of paramount importance to healthcare systems, allowin...
The choice of sentence encoder architecture reflects assumptions about h...
We investigate Relational Graph Attention Networks, a class of models th...
Experimental evidence indicates that simple models outperform complex de...