3 papers
math.AP2026
Large-Time Analysis of the Langevin Dynamics for Energies Fulfilling Polyak-Åojasiewicz Conditions
Massimo Fornasier, Lukang Sun, Rachel Ward
In this work, we take a step towards understanding overdamped Langevin dynamics for the minimization of a general class of objective functions . We establish well-pose…
astro-ph.GA2025
Modeling turbulent and self-gravitating fluids with Fourier neural operators
Keith Poletti, Stella S. R. Offner, Rachel A. Ward
Neural Operators (NOs) are a leading method for surrogate modeling of partial differential equations. Unlike traditional neural networks, which approximate individual functions, NO…
cs.LG2025
Generating synthetic data for neural operators
Erisa Hasani, Rachel A. Ward
Recent advances in the literature show promising potential of deep learning methods, particularly neural operators, in obtaining numerical solutions to partial differential equatio…