Alternatives and similar repositories for physicsnemo-sym

Users that are interested in physicsnemo-sym are comparing it to the libraries listed below

• AmeyaJagtap / XPINNs
  Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…
  ☆224Updated 2 years ago
• shawnrosofsky / PINO_Applications
  Applications of PINOs
  ☆142Updated 3 years ago
• neuraloperator / Geo-FNO
  Geometry-Aware Fourier Neural Operator (Geo-FNO)
  ☆292Updated 6 months ago
• camlab-ethz / poseidon
  Code for the paper "Poseidon: Efficient Foundation Models for PDEs"
  ☆163Updated 8 months ago
• PredictiveIntelligenceLab / jaxpi
  ☆384Updated last month
• ehsanhaghighat / sciann
  Deep learning for Engineers - Physics Informed Deep Learning
  ☆353Updated 2 years ago
• benmoseley / FBPINNs
  Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…
  ☆500Updated 3 weeks ago
• openhackathons-org / End-to-End-AI-for-Science
  This repository containts materials for End-to-End AI for Science
  ☆207Updated last month
• neuraloperator / physics_informed
  ☆497Updated 8 months ago
• camlab-ethz / ConvolutionalNeuralOperator
  This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
  ☆198Updated 3 weeks ago
• mathLab / PINA
  Physics-Informed Neural networks for Advanced modeling
  ☆682Updated this week
• idrl-lab / idrlnet
  IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
  ☆243Updated last year
• PredictiveIntelligenceLab / GradientPathologiesPINNs
  ☆233Updated 4 years ago
• camlab-ethz / AI_Science_Engineering
  This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.
  ☆311Updated 7 months ago
• okada39 / pinn_wave
  Physics Informed Neural Network (PINN) for the wave equation.
  ☆200Updated 5 years ago
• ehsanhaghighat / sciann-applications
  A place to share problems solved with SciANN
  ☆297Updated 2 years ago
• Photon-AI-Research / NeuralSolvers
  Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…
  ☆157Updated 11 months ago
• vc-bonn / Spline_PINN
  ☆117Updated 10 months ago
• quercushernandez / ThermodynamicsGNN
  Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).
  ☆105Updated last year
• levimcclenny / SA-PINNs
  Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]
  ☆261Updated 4 years ago
• neuraloperator / graph-pde
  Using graph network to solve PDEs
  ☆423Updated 6 months ago
• pdearena / pdearena
  ☆279Updated last year
• ComputationalDomain / PINNs
  ☆197Updated 2 years ago
• mdribeiro / DeepCFD
  DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks
  ☆298Updated last year
• chen-yingfa / pinn-torch
  PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations
  ☆125Updated last month
• ikespand / awesome-machine-learning-fluid-mechanics
  Curated list for ML in FM
  ☆226Updated 3 months ago
• alexpapados / Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics
  Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…
  ☆199Updated 2 years ago
• tumaer / JAXFLUIDS
  Differentiable Fluid Dynamics Package
  ☆486Updated 3 weeks ago
• mroberto166 / CAMLab-DLSCTutorials
  ☆212Updated last year
• lu-group / deeponet-fno
  A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
  ☆340Updated 2 years ago