Swiss Equivariant Machine Learning Workshop

Jul 11, 2022, 9:00 until Jul 14, 2022, 17:00, CECAM, Lausanne

Machine learning (ML) based atomistic models are often faced with the challenge of learning physical or chemical properties that have well-defined transformations (equivariance) under translation, rotation,  and reflections of the corresponding atomic structures. The last few

years have seen significant progress on enhancing ML approaches by including symmetry preserving operations, which has led to noteworthy improvements in both the accuracy and data-efficiency of models predicting physical quantities.

A four-day workshop will explore various aspects of the exciting field, including the prediction of tensorial quantities, generative models, theoretical aspects, machine learning interaction potentials and many others. There will be hands-on tutorials as well as discussions, and we particularly encourage the participation of junior researchers.

For more information and to register, please visit:

Registration deadline: June 24! 

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