Graph-based manifold learning and diffusion processes provide a powerful framework for extracting intrinsic geometric features from high-dimensional data. By constructing a graph where nodes represent ...

Atomic environment fingerprints, or structural descriptors, are used to describe the chemical environment around a reference atom. Encoding information such as bond-lengths to neighboring atoms or ...

Machine Learning and Artificial intelligence enable the learning of complex nonlinear patterns from high-dimensional datasets. In ESAM we are interested in leveraging or developing new data-driven ...