Explores enhancing machine learning predictions by refining error metrics and applying constraints for improved accuracy in electron density predictions.
Covers the Calculus of Variations to find ground states in quantum mechanics by minimizing energy, discussing the Euler Lagrange equation and the Fundamental Theorem of Young Measure Theory.
Explores the link between linear algebra and wave mechanics, focusing on operators, self-adjoint nature, Brillouin Zone, and a probabilistic approach to diffusion.
