Towards Foundation Models for Materials Science: The Open MatSci ML Toolkit. - Kin Long Kelvin Lee; Carmelo Gonzales; Matthew Spellings; Mikhail Galkin 001; Santiago Miret; Nalini Kumar (SC Workshops, 2023)

MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling. - Kin Long Kelvin Lee; Carmelo Gonzales; Marcel Nassar; Matthew Spellings; Mikhail Galkin 001; Santiago Miret (CoRR, 2023)

ρ-Diffusion: A diffusion-based density estimation framework for computational physics. - Maxwell X. Cai; Kin Long Kelvin Lee (CoRR, 2023)

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science. - Santiago Miret; Kin Long Kelvin Lee; Carmelo Gonzales; Marcel Nassar; Matthew Spellings (Trans. Mach. Learn. Res., 2023)

Artificial Intelligence for Scientific Discovery at High-Performance Computing Scales. - Kin Long Kelvin Lee; Nalini Kumar (Computer, 2023)

Deconstructing equivariant representations in molecular systems. - Kin Long Kelvin Lee; Michael Galkin; Santiago Miret (CoRR, 2024)

Accelerating Quantum Emitter Characterization with Latent Neural Ordinary Differential Equations. - Andrew H. Proppe; Kin Long Kelvin Lee; Weiwei Sun; Chantalle J. Krajewska; Oliver Tye; Moungi G. Bawendi (CoRR, 2024)

Stiefel Flow Matching for Moment-Constrained Structure Elucidation. - Austin Henry Cheng; Alston Lo; Kin Long Kelvin Lee; Santiago Miret; Alán Aspuru-Guzik (ICLR, 2025)

SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models. - Daniel Levy; Siba Smarak Panigrahi; Sékou-Oumar Kaba; Qiang Zhu; Kin Long Kelvin Lee; Mikhail Galkin 001; Santiago Miret; Siamak Ravanbakhsh (ICLR, 2025)

Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials. - Santiago Miret; Kin Long Kelvin Lee; Carmelo Gonzales; Sajid Mannan; N. M. Anoop Krishnan (CoRR, 2025)