Machine Learning for Molecular Systems

Classical machine learning is reaching its limits, and scientists must develop new models to better understand and use molecular data. The DFG’s Priority Program, “Use and Development of Machine Learning for Molecular Applications – Molecular Machine Learning,” is attempting to achieve just that.

The challenge of representing and calculating the properties of molecules in a computer is that we first have to generate new data instead of working with existing data. The research group applies the so-called “multi-fidelity approach” of machine learning, which combines data of varying accuracy.

The attraction of this Priority Program lies not only in gaining new insights into their particular fields but also in the interdisciplinary exchange with colleagues throughout Germany. More than a dozen universities and research institutions are working together on the program coordinated by Professor Frank Glorius of the University of Münster. Stay tuned for results.

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