Recent advances in generative AI have brought incredible breakthroughs i...
Unsupervised representation learning with variational inference relies
h...
Deep learning models often need sufficient supervision (i.e. labelled da...
Knowledge distillation in neural networks refers to compressing a large ...
We present a comprehensive evaluation of Parameter-Efficient Fine-Tuning...
Pathological brain lesions exhibit diverse appearance in brain images, i...
Discovering causal relations from observational data becomes possible wi...
Learning disentangled representations requires either supervision or the...
Reducing the requirement for densely annotated masks in medical image
se...
Training medical image segmentation models usually requires a large amou...
Causal machine learning (CML) has experienced increasing popularity in
h...
Data augmentation has been widely used in deep learning to reduce
over-f...
We consider the task of counterfactual estimation from observational ima...
Disentangled representation learning has been proposed as an approach to...