Deep learning for DFT
In Density Functional Theory, the exchange correlation functional captures the complex relationship between its input—the electron density — and its output: the exchange-correlation energy. The electron density is represented as a large, irregular point cloud, where each point encodes local information such as the density itself and its gradient. An accurate functional must capture intricate non-local interactions across the electron density, at manageable computational cost.
Read more about DFT: https://www.rarnonalumber.com/en-us/research/blog/breaking-bonds-breaking-ground-advancing-the-accuracy-of-computational-chemistry-with-deep-learning/
