Topic: physics-informed-neural-networks Goto Github

👇 Here are 156 public repositories matching this topic...

314arhaam / burger-pinn
physics-informed-neural-networks,A Physics-Informed Neural Network for solving Burgers' equation.
User: 314arhaam
machine-learning physics-informed-neural-networks burgers-equation deep-learning neural-network

314arhaam / heat-pinn
physics-informed-neural-networks,A Physics-Informed Neural Network to solve 2D steady-state heat equation.
User: 314arhaam
physics-informed-neural-networks physics-informed-ml heat-transfer heat-equation machine-learning deep-learning chemical-engineering process-engineering finite-difference partial-differential-equations

ai4sim / model-collection
physics-informed-neural-networks,This project contains a collection of deep learning models developed by the AI4Sim team with various partners. This is is structured on the basis of use-cases providing canonical PyTorch Lightning pipelines allowing to train neural network models that are able to surrogate various physical processes.
Organization: ai4sim
physics-informed-neural-networks simulation deep-learning neural-networks eviden

akapet00 / locally-adaptive-activation-functions
physics-informed-neural-networks,Simplified implementation of locally adaptive activation functions (LAAF) with slope recovery for deep and physics-informed neural networks (PINNs) in PyTorch.
User: akapet00
poisson-equation adaptive-activation-functions physics-informed-neural-networks deep-learning paper-implementations scientific-computing scientific-machine-learning

alexpapados / physics-informed-deep-learning-solid-and-fluid-mechanics
physics-informed-neural-networks,Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems
User: alexpapados
pinns computational-fluid-dynamics computational-physics physics-informed-neural-networks physics-based-simulation linear-elasticity hydrodynamics shock-tube

amirmardan / pinn_fwi
physics-informed-neural-networks,PINN-FWI: performing physics-informed neural network for FWI
User: amirmardan
Home Page: https://amirmardan.github.io/pinn_fwi/
full-waveform-inversion fwi physics-informed-neural-networks pinn seismic pinn-fwi

asem000 / physics-informed-neural-network-in-jax
physics-informed-neural-networks,Example problems in Physics informed neural network in JAX
User: asem000
colab jax laplace navier-stokes physics-based-neuralnetwork physics-informed-neural-networks pinn

benmoseley / fbpinns
physics-informed-neural-networks,Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
User: benmoseley
neural-networks differential-equations domain-decomposition jax physics-informed-neural-networks pinns

benmoseley / harmonic-oscillator-pinn
physics-informed-neural-networks,Code accompanying my blog post: So, what is a physics-informed neural network?
User: benmoseley
neural-networks physics-informed-ml physics-informed-neural-networks pinns sciml

clegaard / deep_learning_for_dynamical_systems
physics-informed-neural-networks,
User: clegaard
deep-learning dynamical-systems numerical-simulation ordinary-differential-equations partial-differential-equations physics-informed-neural-networks scientific-machine-learning pytorch

dtu-act / pinn-acoustic-wave-prop
physics-informed-neural-networks,Code for sound field predictions in domains with impedance boundaries. Used for generating results from the paper "Physics-informed neural networks for 1D sound field predictions with parameterized sources and impedance boundaries" by N. Borrel-Jensen, A. P. Engsig-Karup, and C. Jeong.
Organization: dtu-act
physics-informed-neural-networks acoustics impedance-boundary-condition

erfanhamdi / pinn-torch
physics-informed-neural-networks,Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose
User: erfanhamdi
physics-informed-neural-networks pinn pytorch

ibm / simulai
physics-informed-neural-networks,A toolkit with data-driven pipelines for physics-informed machine learning.
Organization: ibm
Home Page: https://ibm.github.io/simulai/
machine-learning neural-networks physics-informed-neural-networks simulation

idrl-lab / idrlnet
physics-informed-neural-networks,IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
Organization: idrl-lab
machine-learning physics-informed-neural-networks scientific-machine-learning pde-solver inverse-problems data-driven-model python

ippqw5 / pinnlearning
physics-informed-neural-networks,Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN
User: ippqw5
deep-learning physics-informed-neural-networks tensorflow2

jbramburger / datadrivendynsyst
physics-informed-neural-networks,Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
User: jbramburger
data-science dynamical-systems dynamic-mode-decomposition physics-informed-neural-networks machine-learning sindy-algorithm sindy autoencoder-neural-network autoencoder autoencoders

juliaepi / mathepideeplearning
physics-informed-neural-networks,Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.
Organization: juliaepi
Home Page: https://juliaepi.github.io/MathEpiDeepLearning/
epidemiological-models mathematical-epidemiology universal-differential-equations neural-differential-equations physics-informed-neural-networks data-driven-model bayesian-inference bayesian-deep-learning probabilistic-machine-learning mathematical-biology

killah-t-cell / plasma.jl
physics-informed-neural-networks,An interface for accelerated simulation of high-dimensional collisionless and electrostatic plasmas.
User: killah-t-cell
plasma-physics vlasov scientific-machine-learning physics-informed-neural-networks vlasov-equation julia nuclear-fusion

lanl / hippynn
physics-informed-neural-networks,python library for atomistic machine learning
Organization: lanl
Home Page: https://lanl.github.io/hippynn/
atomistic-models interatomic-potentials machine-learning physics-informed-neural-networks graph-neural-networks library atomistic-machine-learning

mahindrautela / bopinn
physics-informed-neural-networks,Bayesian optimized physics-informed neural network for parameter estimation
User: mahindrautela
bayesian-optimization physics-informed-neural-networks

martavarela / ep-pinns
physics-informed-neural-networks,EP-PINNs implementation for 1D and 2D forward and inverse solvers for the Aliev-Panfilov cardiac electrophysiology model. Also includes Matlab finite-differences solver for data generation.
User: martavarela
physics-informed-neural-networks biophysics computational-model cardiac-electrophysiology

martinastro / gravnn
physics-informed-neural-networks,Repository for Gravity Field Modeling and Recovery using Machine Learning Methods
User: martinastro
aerospace gravity-model machine-learning physics-informed-neural-networks planetary-science python tensorflow

martinuzzifrancesco / awesome-scientific-machine-learning
physics-informed-neural-networks,A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software
User: martinuzzifrancesco
differential-equations neural-differential-equations scientific-machine-learning sciml physics-informed-learning physics-informed-neural-networks pinn

mathlab / pina
physics-informed-neural-networks,Physics-Informed Neural networks for Advanced modeling
Organization: mathlab
Home Page: https://mathlab.github.io/PINA/
deep-learning differential-equations equation-learning hacktoberfest lightining machine-learning modeling neural-networks neural-operators ode pde physics-informed physics-informed-neural-networks pinn python pytorch

mjfadeaway / das
physics-informed-neural-networks,DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations
User: mjfadeaway
Home Page: https://arxiv.org/abs/2112.14038
adaptive-sampling deep-generative-models physics-informed-neural-networks scientific-machine-learning partial-differential-equations pde deep-learning pinn

nanditadoloi / pinn
physics-informed-neural-networks,Simple PyTorch Implementation of Physics Informed Neural Network (PINN)
User: nanditadoloi
physics-informed-neural-networks pytorch machine-learning

neo-fetch / nvidia-modulus-airfoil-optimisation
physics-informed-neural-networks,Using NVIDIA modulus for airfoil optimizations at different angles.
User: neo-fetch
simnet nvidia nvidia-modulus pinns physics-simulation physics physics-informed-neural-networks nvidia-simnet fluid-dynamics computational-physics

neurodiffgym / neurodiffeq
physics-informed-neural-networks,A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
Organization: neurodiffgym
Home Page: http://pypi.org/project/neurodiffeq/
differential-equations neural-networks pytorch pde-solver odes artificial-intelligence deep-learning physics-informed-neural-networks pypi time-series

nimahsn / pinns_tf2
physics-informed-neural-networks,Yet another PINN implementation
User: nimahsn
pinns physics-informed-neural-networks tensorflow

ofdatacommittee / ofmlhackathon
physics-informed-neural-networks,OpenFOAM and Machine Learning Hackathon
Organization: ofdatacommittee
deep-reinforcement-learning hackathon machine-learning nvidia-modulus openfoam physics-informed-neural-networks smartsim

openhackathons-org / end-to-end-ai-for-science
physics-informed-neural-networks,This repository containts materials for End-to-End AI for Science
Organization: openhackathons-org
ai artificial-intelligence fourcastnet hpc modulus navier-stokes omniverse pde physics-informed-neural-networks pinn

panchgonzalez / nmor
physics-informed-neural-networks,Deep learning framework for model reduction of dynamical systems
User: panchgonzalez
Home Page: https://arxiv.org/abs/1808.01346
dimensionality-reduction tensorflow scientific-computing dynamical-systems physics-informed-neural-networks

pdebench / pdebench
physics-informed-neural-networks,PDEBench: An Extensive Benchmark for Scientific Machine Learning
Organization: pdebench
ai benchmark jax machine-learning pytorch scientific scientific-computing sciml simulation deep-learning

pkestene / ms-hpc-ai-gpu
physics-informed-neural-networks,resources pour le cours d'introduction à la programmation des GPUs du mastère spécialisé HPC-AI
User: pkestene
cuda deep-learning gpu gpu-computing machine-learning physics-informed-neural-networks pinn pinns

rezaakb / pinns-tf2
physics-informed-neural-networks,PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.
User: rezaakb
physics physics-informed-neural-networks pinns tensorflow2

rezaakb / pinns-torch
physics-informed-neural-networks,PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
User: rezaakb
cuda-graph jit-compiler physics-informed-neural-networks pinns pytorch

rmojgani / lpinns
physics-informed-neural-networks,To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to the direction of travel of information in convection-diffusion equations, i.e., method of characteristic; The repository includes a pytorch implementation of PINN and proposed LPINN with periodic boundary conditions
User: rmojgani
ml nn pinn burgers convection convection-diffusion lagrangian method-of-characteristics physics-informed-neural-networks deep-learning

sciml / scimltutorialsoutput
physics-informed-neural-networks,Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLTutorialsOutput/stable/
differential-equations julia neural-differential-equations neural-ode ode physics-informed-learning physics-informed-ml physics-informed-neural-networks scientific-machine-learning sciml

sgrubas / nes
physics-informed-neural-networks,Neural Eikonal Solver: framework for modeling traveltimes via solving eikonal equation using neural networks
User: sgrubas
Home Page: https://sgrubas.github.io/NES/
caustics eikonal-equation eikonal-solver physics-informed-neural-networks traveltime neural-eikonal-solver

shashanksubramanian / adaptive-selfsupervision-pinns
physics-informed-neural-networks,Gradient-based adaptive sampling algorithms for self-supervising PINNs
User: shashanksubramanian
adaptive-sampling physics-informed-neural-networks scientific-machine-learning

shengfeng233 / pinn-for-ns-equation
physics-informed-neural-networks,A pytorch implementaion of physics informed neural networks for two dimensional NS equation
User: shengfeng233
pytorch fluid-mechanics physics-informed-neural-networks

skoohy / gpt-pinn
physics-informed-neural-networks,Generative Pre-Trained Physics-Informed Neural Networks Implementation
User: skoohy
deep-learning machine-learning neural-network pdes physics-informed-learning physics-informed-neural-networks pinn pytorch tensorflow allen-cahn

tensordiffeq / tensordiffeq
physics-informed-neural-networks,Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Organization: tensordiffeq
Home Page: http://docs.tensordiffeq.io
pinns scientific-machine-learning tensorflow tensorflow2 physics-informed-learning physics-informed-neural-networks gpu gpu-computing gpu-acceleration multi-gpu

thaipduong / se3hamdl
physics-informed-neural-networks,Code for our RSS'21 paper: "Hamiltonian-based Neural ODE Networks on the SE(3) Manifold For Dynamics Learning and Control"
User: thaipduong
Home Page: https://thaipduong.github.io/SE3HamDL/
neural-ode dynamics-learning trajectory-tracking physics-informed-neural-networks

ucl-bug / jwave
physics-informed-neural-networks,A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs
Organization: ucl-bug
jax simulation acoustics differentiable-simulations physics-informed-neural-networks scientific-machine-learning gpu-acceleration kwave ultrasound wave-equation

viktorc / pararealml
physics-informed-neural-networks,A machine learning boosted parallel-in-time differential equation solver framework.
User: viktorc
differential-equations machine-learning parareal parallel-in-time hpc ode-solver pde-solver parallel-computing scientific-computing physics

vlar-group / nvfi
physics-informed-neural-networks,NVFi in PyTorch (NeurIPS 2023)
Organization: vlar-group
3d 3d-reconstruction 3d-rendering neurips neurips-2023 physics-3d physics-informed-learning physics-informed-neural-networks velocity 3d-physics-learning

wagenaartje / pinn4hcf
physics-informed-neural-networks,Physics-informed neural networks for highly compressible flows 🧠🌊
User: wagenaartje
Home Page: https://repository.tudelft.nl/islandora/object/uuid:6fd86786-153e-4c98-b4e2-8fa36f90eb2a
compressible-fluid-dynamics entropy euler-equations failure-modes physics-informed-neural-networks shock-capturing supersonic-flow

xinyuanliao / adaptive-optimization-of-pinn
physics-informed-neural-networks,Optimizing Physics-Informed NN using Multi-task Likelihood Loss Balance Algorithm and Adaptive Activation Function Algorithm
User: xinyuanliao
adaptive-activation-function-algorithm deep-learning multi-task-likelihood-loss-balance-algorithm physics-informed-neural-networks

xinyuanliao / attnpinn-for-rul-estimation
physics-informed-neural-networks,A Framework for Remaining Useful Life Prediction Based on Self-Attention and Physics-Informed Neural Networks
User: xinyuanliao
physics-informed-neural-networks remaining-useful-life-prediction self-attention