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Machine Learning meets Quantum Physics

BIFOLD researchers contributed to an in-depth referenced work on the physics-based machine learning techniques that model electronic and atomistic properties of matter.

Machine Learning Meets Quantum Physics” [Schütt, K.T., Chmiela, S., von Lilienfeld, O.A., Tkatchenko, A., Tsuda, K., Müller, K.-R. (Eds.)] was published in “Lecture Notes in Physics” (Springer)

Our book Machine Learning meets Quantum Physics gives an overview of this flourishing interdisciplinary research field between ML, AI, physics and quantum chemistry. It is intended as a versatile blend of both introductory and advanced materials for researchers from the natural sciences (Physics and Chemistry), computer scientists (Machine Learning and AI) and engineers alike. The book provides a broad and hopefully balanced snapshot in time of a highly active field that is experiencing a large growth of interest.”

Prof. Dr. Klaus-Robert Müller / Director BIFOLD

Read Prof. Dr. Müller’s full message in Springer’s “Quantum Science and Technology” blog!