Residual Multi-Fidelity Neural Network Computing

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Residual Multi-Fidelity Neural Network Computing

5 October 2023

Mohammad Motamed

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Papers citing "Residual Multi-Fidelity Neural Network Computing"

14 / 14 papers shown

Title
Approximation Error and Complexity Bounds for ReLU Networks on Low-Regular Function Spaces Owen Davis Gianluca Geraci Mohammad Motamed 61 2 0 10 May 2024
Multi-fidelity surrogate modeling using long short-term memory networks Paolo Conti Mengwu Guo Andrea Manzoni J. Hesthaven AI4CE 63 48 0 05 Aug 2022
Approximation Power of Deep Neural Networks: an explanatory mathematical survey Mohammad Motamed 32 3 0 19 Jul 2022
Multifidelity data fusion in convolutional encoder/decoder networks Lauren Partin Gianluca Geraci A. Rushdi M. Eldred Daniele E. Schiavazzi UQCV AI4CE 50 14 0 10 May 2022
Multifidelity Deep Operator Networks For Data-Driven and Physics-Informed Problems Amanda A. Howard M. Perego G. Karniadakis P. Stinis AI4CE 74 56 0 19 Apr 2022
Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities Mengwu Guo Andrea Manzoni Maurice Amendt Paolo Conti J. Hesthaven 143 97 0 26 Feb 2021
Multi-fidelity Bayesian Neural Networks: Algorithms and Applications Xuhui Meng H. Babaee George Karniadakis 54 131 0 19 Dec 2020
The gap between theory and practice in function approximation with deep neural networks Ben Adcock N. Dexter 57 94 0 16 Jan 2020
Nonlinear Approximation and (Deep) ReLU Networks Ingrid Daubechies Ronald A. DeVore S. Foucart Boris Hanin G. Petrova 100 142 0 05 May 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs Gitta Kutyniok P. Petersen Mones Raslan R. Schneider 87 198 0 31 Mar 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 86 200 0 21 Feb 2019
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 123 1,389 0 30 Sep 2017
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 246 16,377 0 30 Apr 2014
Practical recommendations for gradient-based training of deep architectures Yoshua Bengio 3DH ODL 193 2,201 0 24 Jun 2012