4 citations · 4 across the 6 of their papers we have counts for
7 papers
A Sharp Norm Inequality and Buzano's Inequality via Determinants
Jose Antonio Lara Benitez
We give a short linear-algebraic proof of the inequality valid for every . This inequality relate…
Neural Operators Can Discover Functional Clusters
Yicen Li, Jose Antonio Lara Benitez, Ruiyang Hong +3
Operator learning is reshaping scientific computing by amortizing inference across infinite families of problems. While neural operators (NOs) are increasingly well understood for…
Hybrid operator learning of wave scattering maps in high-contrast media
Advait Balaji, Trevor Teolis, S. David Mis +3
Surrogate modeling of wave propagation and scattering (i.e. the wave speed and source to wave field map) in heterogeneous media has significant potential in applications such as se…
Neural equilibria for long-term prediction of nonlinear conservation laws
J. Antonio Lara Benitez, Kareem Hegazy, Junyi Guo +3
Nonlinear conservation laws govern a broad class of important physical systems in science and industry and are central to scientific machine learning (SciML). Large general-purpose…
Mixtures of Neural Operators Reduce Active Complexity in Operator Learning
Anastasis Kratsios, Takashi Furuya, Jose Antonio Lara Benitez +2
Operator-learning systems are not governed solely by total parameter count; for one query, the relevant bottleneck can be the model that must be loaded and evaluated. We study this…
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation
J. Antonio Lara Benitez, Takashi Furuya, Florian Faucher +3
Despite their remarkable success in approximating a wide range of operators defined by PDEs, existing neural operators (NOs) do not necessarily perform well for all physics problem…