Deep Learning Spectroscopy (Kunal Ghosh)

Spectroscopy is central to the natural sciences and engineering as one of the primary methods to investigate the real world. We show that deep learning methods can learn to predict spectra (particularly photoemission spectra) directly from the structures of molecules. We show an application of this model in searching for interesting molecules in a different dataset and spend some time talking about the drawbacks of this method and future work. This talk is part of the Discussion meeting on Machine Learning (), organised by the GDR REST.