As an important methodology to measure distribution discrepancy, optimal transport (OT)
has been successfully applied to learn generalizable visual models under changing …

In many machine learning applications on signals and biomedical data, especially
electroencephalogram (EEG), one major challenge is the variability of the data across …

Weakly Supervised Object Localization (WSOL) allows for training deep learning models for
classification and localization, using only global class-level labels. The lack of bounding box …

Test-Time Adaptation (TTA) has recently emerged as a promising strategy for tackling the
problem of machine learning model robustness under distribution shifts by adapting the …