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Safety and reliability in ML systems

Data-driven automation requires methods ensuring the safety of systems and their users. Results must be reproducible

Efficient Machine Learning

Modern AI suffers from ever-increasing costs in time, infrastructure and energy. Efficient methods requiring less data and computation are …

Trustworthy and interpretable ML

Automating decisions based on data is a multifaceted problem with many pitfalls. We tackle multiple ends of the spectrum, from the detection …

Advances and fundamentals in ML

As in any science, fertility in Machine Learning also comes from cross-pollination. Keeping an eye open for interesting development across …