Abstract Interest in Machine Learning applications to tackle clinical and biological problems
is increasing. This is driven by promising results reported in many research papers, the …

Abstract Machine learning models always make a prediction, even when it is likely to be
inaccurate. This behavior should be avoided in many decision support applications, where …

Electricity, a fundamental commodity, must be generated as per required utilization which
cannot be stored at large scales. The production cost heavily depends upon the source such …

With the advancement in cutting-edge technology, a huge volume of data is generated every
day. Data science is one of the unique and most motivating area of research which is …

Anomaly detection aims at detecting unexpected behaviours in the data. Because anomaly
detection is usually an unsupervised task, traditional anomaly detectors learn a decision …

Uncertainty is ubiquitous and happens in every single prediction of Machine Learning
models. The ability to estimate and quantify the uncertainty of individual predictions is …

In medicine, early detection of lung cancer is essential for successful treatment regimens.
Despite the small sample size, cancer databases often include gene expression levels as …

Anomaly detection methods aim to identify examples that do not follow the expected
behavior. For various reasons, anomaly detection is typically tackled by using unsupervised …

Uncertainty is an inevitable and essential aspect of the worldwe live in and a fundamental
aspect of human decision-making. It is no different in the realm of machine learning. Just as …

Le monde vit de multiples crises environnementales: changements climatiques, perte de
biodiversité, dégradation des sols, pollution,... Les villes peuvent parfois être vues comme …