Alternatives and similar repositories for Turbulent-Flow-Nets

Users that are interested in Turbulent-Flow-Nets are comparing it to the libraries listed below

• echowve / phygnnet
  Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"
  ☆51Updated 2 years ago
• Raocp / PeRCNN
  Physics-encoded recurrent convolutional neural network
  ☆46Updated 3 years ago
• lu-group / mionet
  MIONet: Learning multiple-input operators via tensor product
  ☆38Updated 2 years ago
• Rose-STL-Lab / Turbulent-Flow-Net
  Turbulent flow network source code
  ☆70Updated 7 months ago
• lu-group / deeponet-extrapolation
  Reliable extrapolation of deep neural operators informed by physics or sparse observations
  ☆27Updated 2 years ago
• csccm-iitd / WNO
  ☆62Updated 2 months ago
• cics-nd / ar-pde-cnn
  Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
  ☆93Updated 3 years ago
• cwq2016 / POD-PINN
  POD-PINN code and manuscript
  ☆54Updated 11 months ago
• jx-wang-s-group / ppnn
  PDE Preserved Neural Network
  ☆57Updated 5 months ago
• BaratiLab / ROMER
  Reduced-Order Modeling of Fluid Flows with Transformers
  ☆24Updated 2 years ago
• PredictiveScienceLab / variational-elliptic-SPDE
  ☆13Updated 5 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…
  ☆56Updated 9 months ago
• scaomath / torch-cfd
  [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch
  ☆62Updated 4 months ago
• mario-linov / graphs4cfd
  Graph Neural Networks (GNN) based solvers for Computational Fluid Dynamics (CFD)
  ☆44Updated last year
• PredictiveIntelligenceLab / Long-time-Integration-PI-DeepONets
  ☆55Updated 3 years ago
• Jianxun-Wang / phygeonet
  PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain
  ☆88Updated 4 years ago
• fpichi / gca-rom
  GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.
  ☆36Updated last month
• cfl-minds / gnn_laminar_flow
  Laminar flow prediction using graph neural networks
  ☆31Updated 9 months ago
• rbischof / relative_balancing
  ☆64Updated 2 years ago
• somdattagoswami / Approximating-StiffKinetics
  ☆12Updated last year
• CarlosJose126 / NeuralODE-ROM
  This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"
  ☆18Updated 2 years ago
• katiana22 / latent-deeponet
  Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
  ☆72Updated 6 months ago
• fyang235 / Deep-Learning-Turbulence-model
  Use deep learning to learn a turbulence model from high fedelity data. The model can reasonably predict other turbulent flows.
  ☆22Updated 6 years ago
• Jianxun-Wang / LabelFree-DNN-Surrogate
  Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
  ☆92Updated 2 years ago
• AdrianDario10 / Navier_Stokes_cylinder2D
  Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation
  ☆33Updated 3 years ago
• Jianxun-Wang / graphGalerkin
  Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
  ☆56Updated 3 years ago
• junfeng-chen / position_induced_transformer
  PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations
  ☆24Updated 4 months ago
• paulpuren / PhySR
  Physics-informed deep super-resolution of spatiotemporal data
  ☆47Updated 2 years ago
• JohnCSu / DeepONet_Pytorch_Demo
  Simple demo on implementing data driven and physics informed Deep O Nets in pytorch
  ☆19Updated last year
• abihlo / pinnsSWE
  ☆19Updated 4 years ago