4 papers
Generative clinical time series models trained on moderate amounts of patient data are privacy preserving
Rustam Zhumagambetov, Niklas Giesa, Sebastian D. Boie +1
Sharing medical data for machine learning model training purposes is often impossible due to the risk of disclosing identifying information about individual patients. Synthetic dat…
Explainable AI needs formalization
Stefan Haufe, Rick Wilming, Benedict Clark +4
The field of "explainable artificial intelligence" (XAI) seemingly addresses the desire that decisions of machine learning systems should be human-understandable. However, in its c…
A biologically-inspired multi-modal evaluation of molecular generative machine learning
Elizaveta Vinogradova, Abay Artykbayev, Alisher Amanatay +10
While generative models have recently become ubiquitous in many scientific areas, less attention has been paid to their evaluation. For molecular generative models, the state-of-th…
Rooting Formal Methods within Higher Education Curricula for Computer Science and Software Engineering -- A White Paper
Antonio Cerone, Markus Roggenbach, James Davenport +10
This white paper argues that formal methods need to be better rooted in higher education curricula for computer science and software engineering programmes of study. To this end, i…