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An extended physics informed neural network for preliminary analysis of
  parametric optimal control problems

An extended physics informed neural network for preliminary analysis of parametric optimal control problems

26 October 2021
N. Demo
M. Strazzullo
G. Rozza
    PINN
ArXivPDFHTML

Papers citing "An extended physics informed neural network for preliminary analysis of parametric optimal control problems"

12 / 12 papers shown
Title
Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks
Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks
A. Celaya
Yimo Wang
David T. Fuentes
Beatrice Riviere
38
0
0
12 Feb 2025
Real-time optimal control of high-dimensional parametrized systems by
  deep learning-based reduced order models
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models
Matteo Tomasetto
Andrea Manzoni
Francesco Braghin
AI4CE
13
1
0
09 Sep 2024
Learning solutions of parametric Navier-Stokes with physics-informed
  neural networks
Learning solutions of parametric Navier-Stokes with physics-informed neural networks
M. Naderibeni
Marcel J. T. Reinders
L. Wu
David Tax
PINN
10
2
0
05 Feb 2024
TSONN: Time-stepping-oriented neural network for solving partial
  differential equations
TSONN: Time-stepping-oriented neural network for solving partial differential equations
W. Cao
Weiwei Zhang
AI4TS
11
1
0
25 Oct 2023
Solving Elliptic Optimal Control Problems via Neural Networks and
  Optimality System
Solving Elliptic Optimal Control Problems via Neural Networks and Optimality System
Yongcheng Dai
Bangti Jin
R. Sau
Zhi Zhou
14
4
0
23 Aug 2023
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast
  and Accurate Prediction of Partial Differential Equations
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations
Bin Shan
Ye Li
Sheng-Jun Huang
PINN
8
2
0
30 Nov 2022
Multi-fidelity surrogate modeling using long short-term memory networks
Multi-fidelity surrogate modeling using long short-term memory networks
Paolo Conti
Mengwu Guo
Andrea Manzoni
J. Hesthaven
AI4CE
17
48
0
05 Aug 2022
Investigation of Physics-Informed Deep Learning for the Prediction of
  Parametric, Three-Dimensional Flow Based on Boundary Data
Investigation of Physics-Informed Deep Learning for the Prediction of Parametric, Three-Dimensional Flow Based on Boundary Data
Philipp Heger
Markus Full
Daniel Hilger
N. Hosters
AI4CE
9
9
0
17 Mar 2022
Multi-fidelity regression using artificial neural networks: efficient
  approximation of parameter-dependent output quantities
Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities
Mengwu Guo
Andrea Manzoni
Maurice Amendt
Paolo Conti
J. Hesthaven
68
95
0
26 Feb 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
170
755
0
13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain
  Decomposition
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition
E. Kharazmi
Zhongqiang Zhang
George Karniadakis
113
503
0
11 Mar 2020
All-Optical Machine Learning Using Diffractive Deep Neural Networks
All-Optical Machine Learning Using Diffractive Deep Neural Networks
Xing Lin
Y. Rivenson
N. Yardimci
Muhammed Veli
Mona Jarrahi
Aydogan Ozcan
59
1,596
0
14 Apr 2018
1