• DeepXDE

  • Referenced in 61 articles [sw32456]
  • present an overview of physics-informed neural networks (PINNs), which embed a PDE into...
  • FPINNs

  • Referenced in 27 articles [sw40570]
  • fPINNs: Fractional Physics-Informed Neural Networks. Physics-informed neural networks (PINNs) are effective in solving...
  • NeuralPDE.jl

  • Referenced in 33 articles [sw39548]
  • solver package which consists of neural network solvers for partial differential equations using scientific machine ... learning (SciML) techniques such as physics-informed neural networks (PINNs) and deep BSDE solvers. This...
  • NSFnets

  • Referenced in 23 articles [sw42059]
  • NSFnets (Navier-Stokes Flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations ... employ physics-informed neural networks (PINNs) to simulate the incompressible flows ranging from laminar...
  • PINNsNTK

  • Referenced in 17 articles [sw42058]
  • neural tangent kernel perspective. Physics-informed neural networks (PINNs) have lately received great attention thanks...
  • SciANN

  • Referenced in 10 articles [sw38344]
  • scientific computations and physics-informed deep learning using artificial neural networks. In this paper ... scientific computing and physics-informed deep learning using artificial neural networks. SciANN uses the widely ... TensorFlow and Keras to build deep neural networks and optimization models, thus inheriting many ... differential equations (PDE) using the physics-informed neural networks (PINN) architecture, therefore providing the flexibility...
  • TensorDiffEq

  • Referenced in 1 article [sw39549]
  • Forward and Inverse Solvers for Physics Informed Neural Networks. Physics-Informed Neural Networks promise...
  • Stiff-PINN

  • Referenced in 1 article [sw42094]
  • Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics. Recently developed physics-informed neural...
  • IDRLnet

  • Referenced in 1 article [sw39547]
  • IDRLnet: A Physics-Informed Neural Network Library. Physics Informed Neural Network (PINN) is a scientific...
  • PDE-NetGen

  • Referenced in 1 article [sw37737]
  • deep neural network architectures is an open issue. In the spirit of physics-informed ... into neural network architectures. PDE-NetGen combines symbolic calculus and a neural network generator ... plug-and-play tool to generate physics-informed NN architectures. They provide computationally-efficient...
  • Matlab

  • Referenced in 13544 articles [sw00558]
  • MATLAB® is a high-level language and interactive...
  • TISEAN

  • Referenced in 170 articles [sw00967]
  • Practical implementation of nonlinear time series methods: The...
  • FDFD

  • Referenced in 10 articles [sw01172]
  • FDFD: A 3D finite-difference frequency-domain code...
  • L-BFGS-B

  • Referenced in 200 articles [sw01234]
  • Algorithm 778: L-BFGS-B Fortran subroutines for...
  • EnKF

  • Referenced in 408 articles [sw02066]
  • EnKF-The Ensemble Kalman Filter The EnKF is...
  • L-BFGS

  • Referenced in 806 articles [sw03229]
  • Algorithm 778: L-BFGS-B Fortran subroutines for...
  • COMSOL

  • Referenced in 458 articles [sw04091]
  • The COMSOL Multiphysics engineering simulation software environment facilitates...
  • FLUENT

  • Referenced in 440 articles [sw04263]
  • FLUENT is a Computational Fluid Dynamics (CFD) code...
  • FEniCS

  • Referenced in 840 articles [sw04314]
  • The FEniCS Project is a collaborative project for...