16.09.2026
Vincent Fortuin Receives ERC Starting Grant for Reliable Small-Data AI
Advancing Bayesian Deep Learning for Data-Efficient AI
MCML PI Vincent Fortuin has been awarded an ERC Starting Grant for his project “AutoBayes – Unlocking Reliable Small-data AI through Bayesian Deep Learning.” Hosted at the University of Technology Nuremberg (UTN), the project will advance Bayesian deep learning methods that enable AI systems to learn reliably from limited datasets while better quantifying the uncertainty of their predictions.
Many scientific and practical applications face a fundamental challenge: only small amounts of data are available for training AI systems. Through AutoBayes, Fortuin aims to develop data-efficient and reliable machine learning methods that can make effective use of limited data while providing meaningful measures of uncertainty. The ERC Starting Grant provides up to €1.5 million over a maximum of five years and will support the establishment of a dedicated research team.
Related
15.10.2026
When Flatter Is Not Always Better
In their ICML 2026 paper, MCML researchers show why the flattest regions found during neural network training are not always the best.
13.10.2026
Björn Schuller: What Your Voice Reveals About Your Health
MCML PI Björn Schuller explores how AI can analyze the human voice to detect signs of disease and reveal insights into our health.