Publications and Preprints

Selected works

• G.G., J. Hu, L. Lin, Fast Convergence Rates for Subsampled Natural Gradient Algorithms on Quadratic Model Problems, arXiv 2025.
• A. Guzmán-Cordero, F. Dangel, G.G., M. Zeinhofer, Improving Energy Natural Gradient Descent through Woodbury, Momentum, and Randomization, arXiv 2025.
• E. Epperly, G.G., R. Webber, Randomized Kaczmarz with Tail Averaging, arXiv 2024.
• G.G., N. Abrahamsen, L. Lin, A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions, Journal of Computational Physics 2024.
• J. Lin, G.G., L. Lin, Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation, Journal of Computational Physics 2023.
  
  
  

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