machine learning from VR-generated data

New paper posted to the arXiv, which I’m really excited about, where we describe how user-guided real-time interactive quantum mechanics (QM) simulations in virtual reality (iMD-VR) can be used to train neural networks to learn QM energy functions. The paper is entitled “Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality”.

As far as I know, this is the first ever demonstration of real-time interactive QM in VR, something we were able to accomplish through collaboration with Markus Reiher and Alain Vaucher, our colleagues at ETH in Zurich, who worked with us to develop an interface between our VR framework Narupa, and their excellent SCINE quantum chemistry package. Silvia Amabilino and Lars Bratholm have have also done an excellent job making their excellent GPU-accelerated neural network (NN) framework for learning QM potential energy surfaces available as an open-source package on GitHub – see the paper for more details!

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