16 citations · 63 across the 16 of their papers we have counts for
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math.NA2023
Best approximation results and essential boundary conditions for novel types of weak adversarial network discretizations for PDEs
Silvia Bertoluzza, Erik Burman, Cuiyu He
In this paper, we provide a theoretical analysis of the recently introduced weakly adversarial networks (WAN) method, used to approximate partial differential equations in high dim…
eess.IV2023
NODE-ImgNet: a PDE-informed effective and robust model for image denoising
Xinheng Xie, Yue Wu, Hao Ni +1
Inspired by the traditional partial differential equation (PDE) approach for image denoising, we propose a novel neural network architecture, referred as NODE-ImgNet, that combines…
hep-th2023★ 11 cited
p-Adic Statistical Field Theory and Convolutional Deep Boltzmann Machines
W. A. Zúñiga-Galindo, Cuiyu He, B. A. Zambrano-Luna
Understanding how deep learning architectures work is a central scientific problem. Recently, a correspondence between neural networks (NNs) and Euclidean quantum field theories (Q…