305 related articles for article (PubMed ID: 36966712)
1. Deep learning-accelerated computational framework based on Physics Informed Neural Network for the solution of linear elasticity.
Roy AM; Bose R; Sundararaghavan V; Arróyave R
Neural Netw; 2023 May; 162():472-489. PubMed ID: 36966712
[TBL] [Abstract][Full Text] [Related]
2. Gradient Statistics-Based Multi-Objective Optimization in Physics-Informed Neural Networks.
Vemuri SK; Denzler J
Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960365
[TBL] [Abstract][Full Text] [Related]
3. Physics-informed kernel function neural networks for solving partial differential equations.
Fu Z; Xu W; Liu S
Neural Netw; 2024 Apr; 172():106098. PubMed ID: 38199153
[TBL] [Abstract][Full Text] [Related]
4. Physics-informed attention-based neural network for hyperbolic partial differential equations: application to the Buckley-Leverett problem.
Rodriguez-Torrado R; Ruiz P; Cueto-Felgueroso L; Green MC; Friesen T; Matringe S; Togelius J
Sci Rep; 2022 May; 12(1):7557. PubMed ID: 35534639
[TBL] [Abstract][Full Text] [Related]
5. Physics-informed neural networks and functional interpolation for stiff chemical kinetics.
De Florio M; Schiassi E; Furfaro R
Chaos; 2022 Jun; 32(6):063107. PubMed ID: 35778155
[TBL] [Abstract][Full Text] [Related]
6. Constructing Physics-Informed Neural Networks with Architecture Based on Analytical Modification of Numerical Methods by Solving the Problem of Modelling Processes in a Chemical Reactor.
Tarkhov D; Lazovskaya T; Malykhina G
Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679461
[TBL] [Abstract][Full Text] [Related]
7. Physics-informed UNets for discovering hidden elasticity in heterogeneous materials.
Kamali A; Laksari K
J Mech Behav Biomed Mater; 2024 Feb; 150():106228. PubMed ID: 37988884
[TBL] [Abstract][Full Text] [Related]
8. Error estimates and physics informed augmentation of neural networks for thermally coupled incompressible Navier Stokes equations.
Goraya S; Sobh N; Masud A
Comput Mech; 2023 Aug; 72(2):267-289. PubMed ID: 37583614
[TBL] [Abstract][Full Text] [Related]
9. Recipes for when physics fails: recovering robust learning of physics informed neural networks.
Bajaj C; McLennan L; Andeen T; Roy A
Mach Learn Sci Technol; 2023 Mar; 4(1):015013. PubMed ID: 37680302
[TBL] [Abstract][Full Text] [Related]
10. The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?
Markidis S
Front Big Data; 2021; 4():669097. PubMed ID: 34870188
[TBL] [Abstract][Full Text] [Related]
11. A Second-Order Network Structure Based on Gradient-Enhanced Physics-Informed Neural Networks for Solving Parabolic Partial Differential Equations.
Sun K; Feng X
Entropy (Basel); 2023 Apr; 25(4):. PubMed ID: 37190465
[TBL] [Abstract][Full Text] [Related]
12. AI-Aristotle: A physics-informed framework for systems biology gray-box identification.
Ahmadi Daryakenari N; De Florio M; Shukla K; Karniadakis GE
PLoS Comput Biol; 2024 Mar; 20(3):e1011916. PubMed ID: 38470870
[TBL] [Abstract][Full Text] [Related]
13. The New Simulation of Quasiperiodic Wave, Periodic Wave, and Soliton Solutions of the KdV-mKdV Equation via a Deep Learning Method.
Zhang Y; Dong H; Sun J; Wang Z; Fang Y; Kong Y
Comput Intell Neurosci; 2021; 2021():8548482. PubMed ID: 34868298
[TBL] [Abstract][Full Text] [Related]
14. Performance of Fourier-based activation function in physics-informed neural networks for patient-specific cardiovascular flows.
Aghaee A; Khan MO
Comput Methods Programs Biomed; 2024 Apr; 247():108081. PubMed ID: 38428251
[TBL] [Abstract][Full Text] [Related]
15. A Combination of Deep Neural Networks and Physics to Solve the Inverse Problem of Burger's Equation.
Alkhadhr S; Almekkawy M
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():4465-4468. PubMed ID: 34892210
[TBL] [Abstract][Full Text] [Related]
16. Enhancing neurodynamic approach with physics-informed neural networks for solving non-smooth convex optimization problems.
Wu D; Lisser A
Neural Netw; 2023 Nov; 168():419-430. PubMed ID: 37804745
[TBL] [Abstract][Full Text] [Related]
17. The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.
Oladyshkin S; Praditia T; Kroeker I; Mohammadi F; Nowak W; Otte S
Neural Netw; 2023 Sep; 166():85-104. PubMed ID: 37480771
[TBL] [Abstract][Full Text] [Related]
18. A Novel Hybrid Deep Learning Method for Predicting the Flow Fields of Biomimetic Flapping Wings.
Hu F; Tay W; Zhou Y; Khoo B
Biomimetics (Basel); 2024 Jan; 9(2):. PubMed ID: 38392118
[TBL] [Abstract][Full Text] [Related]
19. Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: An investigation of optimal framework based on vascular morphology.
Zhang X; Mao B; Che Y; Kang J; Luo M; Qiao A; Liu Y; Anzai H; Ohta M; Guo Y; Li G
Comput Biol Med; 2023 Sep; 164():107287. PubMed ID: 37536096
[TBL] [Abstract][Full Text] [Related]
20. Deep learning and inverse discovery of polymer self-consistent field theory inspired by physics-informed neural networks.
Lin D; Yu HY
Phys Rev E; 2022 Jul; 106(1-1):014503. PubMed ID: 35974507
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]