CASUS Institute Seminar, Vincent Martinetto, PhD student, University of California, Merced, USA
Vincent is a PhD student in the Chemistry and Chemical Biology program at the University of California, Merced. He obtained his B.S. in chemistry from Santa Clara University where he worked in an organic chemistry lab. He is interested in the development and exploration of Ensemble Density Functional Theory methods.
Abstract of the talk// Kohn-Sham density functional theory is one of the most successful electronic structure methods for molecules and materials, and density-to-potential inversions can provide insights into the exact formalism underlying this approach. This work looks to circumvent normal inversion schemes by employing Physics Informed Neural Nets (PINNs) in their place. PINNs help to improve predictive transferability and reduce the requisite amount of data to properly train a neural network. The structure of a simple convolutional network and its application to three small datasets in 1D will be presented. Next steps for improving the network will be discussed.
Vincent will be talking live in Görlitz. However, as the event is organized in a hybrid format that includes a videoconferencing tool by Zoom Inc., people interested in the topic have the chance to also join the talk remotely. Please ask for the login details via contact@casus.science.