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 ...

When machine learning is used to suggest new potential scientific insights or directions, algorithms sometimes offer ...

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 ...

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 ...