7 citations · 8 across the 4 of their papers we have counts for
3 papers · 1 filter
Solving Functional PDEs with Gaussian Processes and Applications to Functional Renormalization Group Equations
Xianjin Yang, Matthieu Darcy, Matthew Hudes +3
We present an operator learning framework for solving non-perturbative functional renormalization group equations, which are integro-differential equations defined on functionals.…
Operator Learning at Machine Precision
Aras Bacho, Aleksei G. Sorokin, Xianjin Yang +6
Neural operator learning methods have garnered significant attention in scientific computing for their ability to approximate infinite-dimensional operators. However, increasing th…
Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots
Théo Bourdais, Pau Batlle, Xianjin Yang +3
Most problems within and beyond the scientific domain can be framed into one of the following three levels of complexity of function approximation. Type 1: Approximate an unknown f…