Kin Long Kelvin Lee

According to our database, Kin Long Kelvin Lee authored at least 10 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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, February, 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, Santiago Miret, Siamak Ravanbakhsh

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Stiefel Flow Matching for Moment-Constrained Structure Elucidation.

Austin Henry Cheng, Alston Lo, Kin Long Kelvin Lee, Santiago Miret, Alán Aspuru-Guzik

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Deconstructing equivariant representations in molecular systems.

Kin Long Kelvin Lee, Michael Galkin, Santiago Miret

CoRR, 2024

2023

Artificial Intelligence for Scientific Discovery at High-Performance Computing Scales.

Kin Long Kelvin Lee, Nalini Kumar

Computer, April, 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

ρ-Diffusion: A diffusion-based density estimation framework for computational physics.

Maxwell X. Cai, Kin Long Kelvin Lee

CoRR, 2023

MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling.

Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings, Mikhail Galkin, Santiago Miret

CoRR, 2023

Towards Foundation Models for Materials Science: The Open MatSci ML Toolkit.

Kin Long Kelvin Lee, Carmelo Gonzales, Matthew Spellings, Mikhail Galkin, Santiago Miret, Nalini Kumar

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023