4 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…