79 citations · 91 across the 12 of their papers we have counts for
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math.NA2022★ 1 cited
Deep NURBS -- Admissible Physics-informed Neural Networks
Hamed Saidaoui, Luis Espath, Rául Tempone
In this study, we propose a new numerical scheme for physics-informed neural networks (PINNs) that enables precise and inexpensive solution for partial differential equations (PDEs…
math.OC2022
Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization
Andre Carlon, Luis Espath, Raul Tempone
Using quasi-Newton methods in stochastic optimization is not a trivial task given the difficulty of extracting curvature information from the noisy gradients. Moreover, pre-conditi…