D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. - Tianbo Li; Min Lin; Zheyuan Hu 002; Kunhao Zheng; Giovanni Vignale; Kenji Kawaguchi; A. H. Castro Neto; Kostya S. Novoselov; Shuicheng Yan (ICLR, 2023)

Diagonalization without Diagonalization: A Direct Optimization Approach for Solid-State Density Functional Theory. - Tianbo Li; Min Lin; Stephen Dale; Zekun Shi; A. H. Castro Neto; Kostya S. Novoselov; Giovanni Vignale (CoRR, 2024)

Predicting ionic conductivity in solids from the machine-learned potential energy landscape. - Artem Maevskiy; Alexandra Carvalho; Emil Sataev; Volha Turchyna; Keian Noori; Aleksandr Rodin; A. H. Castro Neto; Andrey Ustyuzhanin (CoRR, 2024)