4 accepted papers
ICU (Intensive Care Unit) records comprise heterogeneous multivariate time series sampled at irregular intervals with pervasive missingness, yet clinical applications demand predictive models that are both accurate and interpretable. We present our Graph Attention-based Relational Learning for Inten…
Evaluations of large-scale recognition methods typically focus on overall performance. While this approach is common, it often fails to provide insights into performance across individual classes, which can lead to fairness issues and misrepresentation. Addressing these gaps is crucial for accuratel…
"Open-Set Recognition (OSR) is a problem with mainly practical applications. However, recent evaluations have largely focused on small-scale data and tuning thresholds over the test set, which disregard the real-world operational needs of parameter selection. Thus, we revisit the original goals of O…
Agnostophobia, the fear of the unknown, can be experienced by deep learning engineers while applying their networks to real-world applications. Unfortunately, network behavior is not well defined for inputs far from a networks training set. In an uncontrolled environment, networks face many instance…