10 citations · 11 across the 2 of their papers we have counts for
3 papers
Optimizing Distributed Training on Frontier for Large Language Models
Sajal Dash, Isaac Lyngaas, Junqi Yin +5
Large language models (LLMs) have demonstrated remarkable success as foundational models, benefiting various downstream applications through fine-tuning. Recent studies on loss sca…
Training-free hyperparameter optimization of neural networks for electronic structures in matter
Lenz Fiedler, Nils Hoffmann, Parvez Mohammed +6
A myriad of phenomena in materials science and chemistry rely on quantum-level simulations of the electronic structure in matter. While moving to larger length and time scales has…
Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks
J. Austin Ellis, Lenz Fiedler, Gabriel A. Popoola +5
We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite elec…