Finding Density Functionals with Machine Learning - John C. Snyder; Matthias Rupp; Katja Hansen; Klaus-Robert Müller; Kieron Burke (CoRR, 2011)

Kernels, Pre-images and Optimization. - John C. Snyder; Sebastian Mika; Kieron Burke; Klaus-Robert Müller (Empirical Inference, 2013)

Understanding Machine-learned Density Functionals. - Li Li 060; John C. Snyder; Isabelle M. Pelaschier; Jessica Huang; Uma-Naresh Niranjan; Paul Duncan; Matthias Rupp; Klaus-Robert Müller; Kieron Burke (CoRR, 2014)

Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals. - Kevin Vu; John C. Snyder; Li Li 060; Matthias Rupp; Brandon F. Chen; Tarek Khelif; Klaus-Robert Müller; Kieron Burke (CoRR, 2015)

By-passing the Kohn-Sham equations with machine learning. - Felix Brockherde; Li Li 060; Kieron Burke; Klaus-Robert Müller (CoRR, 2016)

Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics. - Li Li 060; Stephan Hoyer; Ryan Pederson; Ruoxi Sun 002; Ekin D. Cubuk; Patrick Riley 001; Kieron Burke (CoRR, 2020)

Generalizability of density functionals learned from differentiable programming on weakly correlated spin-polarized systems. - Bhupalee Kalita; Ryan Pederson; Li Li 060; Kieron Burke (CoRR, 2021)

Using Machine Learning to Find New Density Functionals. - Bhupalee Kalita; Kieron Burke (CoRR, 2021)