As machine learning methods gain prominence within clinical decision-mak...
Self-supervised learning in vision-language processing exploits semantic...
Causal reasoning provides a language to ask important interventional and...
Multi-modal data abounds in biomedicine, such as radiology images and
re...
We formulate a general framework for building structural causal models (...
This article discusses how the language of causality can shed new light ...
Generalization capability to unseen domains is crucial for machine learn...
This is an empirical study to investigate the impact of scanner effects ...
We investigate discrete spin transformations, a geometric framework to
m...
Current face recognition systems typically operate via classification in...
Revealing latent structure in data is an active field of research, havin...
Current face recognition systems robustly recognize identities across a ...
We present a novel cost function for semi-supervised learning of neural
...
With the adoption of powerful machine learning methods in medical image
...