98 citations · 99 across the 3 of their papers we have counts for
7 papers
FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms
Vahe Gharakhanyan, Yi Yang, Luis Barroso-Luque +24
Molecular crystal structure prediction (CSP) is essential for applications in pharmaceuticals and organic electronics. However, CSP remains challenging and computationally intensiv…
Speculative Sampling For Faster Molecular Dynamics
Arthur Kosmala, Stephan Günnemann, Meng Gao +1
Molecular dynamics (MD) is a key tool for simulating the dynamical behavior of atomic systems. However, MD is inherently serial, which makes it difficult to increase single-system…
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models
Luis Barroso-Luque, Muhammed Shuaibi, Xiang Fu +6
The ability to discover new materials with desirable properties is critical for numerous applications from helping mitigate climate change to advances in next generation computing…
UMA: A Family of Universal Models for Atoms
Brandon M. Wood, Misko Dzamba, Xiang Fu +15
The ability to quickly and accurately compute properties from atomic simulations is critical for advancing a large number of applications in chemistry and materials science includi…
Learning from the electronic structure of molecules across the periodic table
Manasa Kaniselvan, Benjamin Kurt Miller, Meng Gao +2
Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training…
Open Molecular Crystals 2025 (OMC25) Dataset and Models
Vahe Gharakhanyan, Luis Barroso-Luque, Yi Yang +16
The development of accurate and efficient machine learning models for predicting the structure and properties of molecular crystals has been hindered by the scarcity of publicly av…