Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations

2 May 2020

Papers citing "Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations"

13 / 13 papers shown

Title
An efficient hp-Variational PINNs framework for incompressible Navier-Stokes equations T. Anandh Divij Ghose Ankit Tyagi Abhineet Gupta Suranjan Sarkar Sashikumaar Ganesan 35 0 0 06 Sep 2024
Active Learning for Neural PDE Solvers Daniel Musekamp Marimuthu Kalimuthu David Holzmüller Makoto Takamoto Carlos Fernandez AI4CE 57 4 0 02 Aug 2024
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 20 10 0 08 Oct 2023
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Physics-Informed Machine Learning of Argon Gas-Driven Melt Pool Dynamics Rahul Sharma Y.B. Guo M. Raissi W. Guo PINN AI4CE 42 5 0 23 Jul 2023
Investigation of Compressor Cascade Flow Using Physics- Informed Neural Networks with Adaptive Learning Strategy Zhihui Li Francesco Montomoli Sanjiv Sharma PINN 29 6 0 15 Jul 2023
Temporal Consistency Loss for Physics-Informed Neural Networks Sukirt Thakur M. Raissi H. Mitra A. Ardekani PINN 33 10 0 30 Jan 2023
Design of Turing Systems with Physics-Informed Neural Networks J. Kho W. Koh Jian Cheng Wong P. Chiu C. Ooi DiffM AI4CE 19 2 0 24 Nov 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 20 4 0 14 Oct 2022
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 27 9 0 17 Mar 2022
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes Claire E. Heaney Zef Wolffs Jón Atli Tómasson L. Kahouadji P. Salinas A. Nicolle Omar K. Matar Ionel M. Navon N. Srinil Christopher C. Pain AI4CE 29 21 0 13 Feb 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,180 0 14 Jan 2022
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks Filipe de Avila Belbute-Peres Yi-fan Chen Fei Sha PINN 16 38 0 28 Oct 2021