375 citations · 1.3k across the 19 of their papers we have counts for
19 papers
Magnetohydrodynamics Simulations
E. A. Huerta
Magnetohydrodynamics (MHD) couples the Navier--Stokes and Maxwell equations into a nonlinear system of partial differential equations governing stellar interiors, astrophysical jet…
Resolving Turbulent Magnetohydrodynamics: A Hybrid Operator-Diffusion Framework
Semih Kacmaz, E. A. Huerta, Roland Haas
We present a hybrid machine learning framework that combines Physics-Informed Neural Operators (PINOs) with score-based generative diffusion models to simulate the full spatio-temp…
Machine learning-driven conservative-to-primitive conversion in hybrid piecewise polytropic and tabulated equations of state
Semih Kacmaz, Roland Haas, E. A. Huerta
We present a novel machine learning (ML) method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditi…
Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources -- A Case Study on Federated Fine-tuning of LLaMA 2
Zilinghan Li, Shilan He, Pranshu Chaturvedi +4
Federated learning enables multiple data owners to collaboratively train robust machine learning models without transferring large or sensitive local datasets by only sharing the p…
Magnetohydrodynamics with Physics Informed Neural Operators
Shawn G. Rosofsky, E. A. Huerta
The modeling of multi-scale and multi-physics complex systems typically involves the use of scientific software that can optimally leverage extreme scale computing. Despite major d…
MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge
Marlin B. Schäfer, Ondřej Zelenka, Alexander H. Nitz +20
We present the results of the first Machine Learning Gravitational-Wave Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups had to identify gravitationa…