ENS-Data Science colloquium – Michele Ceriotti (EPFL)
ENS Salle DussaneMichele Ceriotti (EPFL) Title: Between physics and scaling: inductive biases in atomistic machine learningAbstract: Machine-learning techniques are often applied to perform "end-to-end" predictions, making black-box estimatesof a property of interest using only a coarse description of the corresponding inputs.In contrast, atomic-scale modeling of matter is most useful when it allows one to gather a mechanistic insightinto the microscopic processes that underlie the behavior of molecules and materials.In this talk I will provide an overview of the progress that has been made combining these two philosophies,using data-driven techniques to build surrogate models […]