6 citations · 6 across the 3 of their papers we have counts for
3 papers
math.NA2026
Neural network approximation in discrete dual norms with adaptive test spaces
Tanakorn Udomworarat, Ignacio Brevis, Kristoffer G. van der Zee +1
In robust variational physics-informed neural networks (RVPINNs), the loss function is formulated in terms of the Riesz representative of the variational residual within a discrete…
math.NA2026
RUNNs: Ritz-Uzawa Neural Networks for Solving Variational Problems
Pablo Herrera, Jamie M. Taylor, Carlos Uriarte +3
Solving Partial Differential Equations (PDEs) using neural networks presents different challenges, including integration errors and spectral bias, often leading to poor approximati…
math.NA2021★ 6 cited
Projection in negative norms and the regularization of rough linear functionals
Felipe Millar, Ignacio Muga, Sergio Rojas +1
In order to construct regularizations of continuous linear functionals acting on Sobolev spaces such as , where and is a Lipschitz domain, we propose…