Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations. - Tian Xie 002; Arthur France-Lanord; Yanming Wang; Jeffrey Lopez; Michael Austin Stolberg; Megan Hill; Graham Michael Leverick; Rafael Gómez-Bombarelli; Jeremiah A. Johnson; Yang Shao-Horn; Jeffrey C. Grossman (CoRR, 2021)

Crystal Diffusion Variational Autoencoder for Periodic Material Generation. - Tian Xie 002; Xiang Fu 005; Octavian-Eugen Ganea; Regina Barzilay; Tommi S. Jaakkola (ICLR, 2022)

Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning. - Xiang Fu 005; Tian Xie 002; Nathan J. Rebello; Bradley D. Olsen; Tommi S. Jaakkola (CoRR, 2022)

MatterGen: a generative model for inorganic materials design. - Claudio Zeni; Robert Pinsler; Daniel Zügner; Andrew Fowler; Matthew Horton; Xiang Fu 005; Sasha Shysheya; Jonathan Crabbé; Lixin Sun; Jake Smith; Ryota Tomioka; Tian Xie 002 (CoRR, 2023)

Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations. - Xiang Fu 005; Zhenghao Wu; Wujie Wang; Tian Xie 002; Sinan Keten; Rafael Gómez-Bombarelli; Tommi S. Jaakkola (Trans. Mach. Learn. Res., 2023)

Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-scale Graph Networks. - Xiang Fu 005; Tian Xie 002; Nathan J. Rebello; Bradley D. Olsen; Tommi S. Jaakkola (Trans. Mach. Learn. Res., 2023)

MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design. - Xiang Fu 005; Tian Xie 002; Andrew S. Rosen; Tommi S. Jaakkola; Jake Smith (ICLR, 2024)

A generative model for inorganic materials design. - Claudio Zeni; Robert Pinsler; Daniel Zügner; Andrew Fowler; Matthew Horton; Xiang Fu 005; Zilong Wang; Aliaksandra Shysheya; Jonathan Crabbé; Shoko Ueda; Roberto Sordillo; Lixin Sun; et al. (Nat., 2025)