Alternatives and similar repositories for Burgers-equation-convection-diffusion-in-2D:

Users that are interested in Burgers-equation-convection-diffusion-in-2D are comparing it to the libraries listed below

• bfly123 / PINN_WE
  Discontinuity Computing Using Physics-Informed Neural Network
  ☆22Updated 10 months ago
• lu-group / mionet
  MIONet: Learning multiple-input operators via tensor product
  ☆31Updated 2 years ago
• cwq2016 / POD-PINN
  POD-PINN code and manuscript
  ☆47Updated 3 months ago
• nimahsn / pinns_tf2
  Yet another PINN implementation
  ☆19Updated 8 months ago
• lu-group / pinn-sampling
  Non-adaptive and residual-based adaptive sampling for PINNs
  ☆67Updated 2 years ago
• Cao-WenBo / TSONN
  ☆20Updated last month
• wagenaartje / pinn4hcf
  Physics-informed neural networks for highly compressible flows 🧠🌊
  ☆24Updated last year
• AmeyaJagtap / XPINNs_TensorFlow-2
  XPINN code written in TensorFlow 2
  ☆27Updated 2 years ago
• Shengfeng233 / PINN-for-turbulence
  A pytorch implementation of several approaches using PINN to slove turbulent flow
  ☆63Updated 10 months ago
• fpichi / gca-rom
  GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.
  ☆32Updated 8 months ago
• lu-group / deeponet-extrapolation
  DeepONet extrapolation
  ☆26Updated last year
• BaratiLab / ROMER
  Reduced-Order Modeling of Fluid Flows with Transformers
  ☆21Updated last year
• AmeyaJagtap / Conservative_PINNs
  We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …
  ☆64Updated 2 years ago
• shamsbasir / investigating_mitigating_failure_modes_in_pinns
  This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…
  ☆17Updated last year
• aaronbuhendwa / twophasePINN
  Physics-informed neural networks for two-phase flow problems
  ☆51Updated 2 years ago
• chiuph / CAN-PINN
  Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)
  ☆25Updated last year
• PredictiveIntelligenceLab / Long-time-Integration-PI-DeepONets
  ☆52Updated 2 years ago
• Jianxun-Wang / graphGalerkin
  Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
  ☆49Updated 3 years ago
• kfukami / CNN-SINDy-MLROM
  Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.
  ☆24Updated 3 years ago
• rmojgani / LPINNs
  To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…
  ☆46Updated 2 years ago
• janiechen8 / DeepLSMethod
  ☆10Updated 4 years ago
• qzhe-mechanics / DataAssi-transport
  ☆13Updated 4 years ago
• erfanhamdi / pinn-torch
  Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose
  ☆45Updated 2 years ago
• ContiPaolo / MultiFidelity_POD
  Multi-fidelity reduced-order surrogate modeling
  ☆19Updated 2 months ago
• saniaki / sequential_PINN
  Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems
  ☆50Updated 4 years ago
• raj-brown / APMA2070
  ☆45Updated last year
• Alexzihaohu / NSFnets
  PINN in solving Navier–Stokes equation
  ☆88Updated 4 years ago
• Extrality / AirfRANS
  In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…
  ☆46Updated last month
• katiana22 / TL-DeepONet
  Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
  ☆67Updated last year
• 314arhaam / burger-pinn
  A Physics-Informed Neural Network for solving Burgers' equation.
  ☆30Updated 10 months ago