Using Normalizing Flows for Seismic Data Interpolation Normalizing Flows are a type of neural network that allow us to map one probability distribution into another.  The advantage of such a technique is that they allow us to relate a simple

Deep Learning Chemistry: extracting chemical features from Graph Convolutional Neural Networks The task of quantum chemistry is to compute chemical properties of molecular compounds from the fundamental laws of quantum mechanics.  This poses a tremendous challenge as the most accurate