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physics-informed-learning

Here are 28 public repositories matching this topic...

lululxvi / deepxde

A library for scientific machine learning and physics-informed learning

deep-learning neural-network tensorflow pytorch operator pde paddle pinn jax scientific-machine-learning multi-fidelity-data physics-informed-learning deeponet

Updated Mar 9, 2023
Python

SciML / DiffEqFlux.jl

Sponsor

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

neural-networks partial-differential-equations differential-equations ordinary-differential-equations differentialequations stochastic-differential-equations delay-differential-equations pinn neural-ode scientific-machine-learning neural-sde neural-pde neural-dde neural-differential-equations stiff-ode scientific-ml scientific-ai neural-jump-diffusions neural-sdes physics-informed-learning

Updated Mar 13, 2023
Julia

SciML / DiffEqDocs.jl

Sponsor

Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem

ode dde differential-equations sde dae hacktoberfest neural-ode scientific-machine-learning sciml physics-informed-learning

Updated Mar 13, 2023
Julia

tensordiffeq / TensorDiffEq

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

distributed-systems tensorflow gpu neural-networks gpu-acceleration differential-equations gpu-computing multi-gpu collocation tensorflow2 multi-gpu-training scientific-machine-learning neural-pde pinns physics-informed-learning physics-informed-neural-networks

Updated Mar 1, 2022
Python

SciML / QuasiMonteCarlo.jl

Sponsor

Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)

julia parameter-estimation quasi-monte-carlo scientific-machine-learning sciml physics-informed-learning

Updated Mar 14, 2023
Julia

Raocp / PINN-elastodynamics

physics-informed neural network for elastodynamics problem

neural-network tensorflow elasticity physics-simulation physics-informed-learning

Updated Jan 20, 2022
Python

levimcclenny / SA-PINNs

Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]

deep-learning neural-network tensorflow scientific-computing neural-networks pdes sciml pinns physics-informed-learning adaptive-pinns stiff-pdes

Updated Oct 12, 2021
Python

SciML / sciml.ai

Sponsor

The SciML Scientific Machine Learning Software Organization Website

machine-learning julia julia-language ode dde differential-equations sde dae julialang franklin neural-ode scientific-machine-learning sciml physics-informed-learning

Updated Feb 22, 2023
CSS

katiana22 / TL-DeepONet

Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.

regression partial-differential-equations transfer-learning hilbert-spaces multi-task-learning physics-informed-learning operator-learning deeponet

Updated Jan 15, 2023
Python

SciML / SciMLTutorialsOutput

Sponsor

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

julia ode differential-equations neural-ode scientific-machine-learning neural-differential-equations sciml physics-informed-learning physics-informed-neural-networks physics-informed-ml

Updated Mar 4, 2023
HTML

SciML / PDERoadmap

Sponsor

A repository for the discussion of PDE tooling for scientific machine learning (SciML) and physics-informed machine learning

scientific-machine-learning sciml physics-informed-learning

Updated Nov 21, 2019
Jupyter Notebook

SciML / TensorFlowDiffEq.jl

Sponsor

Using TensorFlow for physics-informed neural networks for scientific machine learning (SciML)

python tensorflow julia differential-equations scientific-machine-learning sciml physics-informed-learning

Updated Nov 30, 2020
Julia

paulpuren / PhySR

Physics-informed deep super-resolution of spatiotemporal data

partial-differential-equations spatiotemporal super-resolution convlstm scientific-machine-learning physics-informed-learning

Updated Dec 18, 2022
Python

jbramburger / DataDrivenDynSyst

Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

data-science machine-learning neural-network forecasting autoencoder dynamical-systems kernel-methods conservation-laws autoencoders sindy dynamic-mode-decomposition time-delay stroboscopic-map poincare-map autoencoder-neural-network extended-dynamic-mode-decomposition physics-informed-learning sindy-algorithm physics-informed-neural-networks universal-approximation-theorem

Updated Mar 8, 2023
Jupyter Notebook

paulpuren / PhyCRNet

Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

simulation partial-differential-equations autoregressive convlstm encoder-decoder-architecture physics-informed-learning residual-connections

Updated Dec 24, 2021
Python

SmartTensors / NMFk.jl

Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning

machine-learning julia feature-extraction scientific-computing blind-source-separation unsupervised-machine-learning scientific-machine-learning source-identification physics-informed-learning

Updated Mar 11, 2023
HTML

MartinuzziFrancesco / awesome-scientific-machine-learning

A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software

differential-equations pinn scientific-machine-learning neural-differential-equations sciml physics-informed-learning physics-informed-neural-networks

Updated Nov 12, 2022

coursekevin / weakformghnn

Weak For Generalized Hamiltonian Learning

time-series physics-informed-learning

Updated Feb 13, 2021
Jupyter Notebook

SmartTensors / SmartTensorsTutorials.jl

Smart Tensors Tutorials

machine-learning julia julia-language tutorials feature-selection scientific-computing blind-source-separation scientific-machine-learning source-identification physics-informed-learning

Updated Dec 11, 2022
Jupyter Notebook

Deep-LFM

tomcdonald / Deep-LFM

Code for the NeurIPS 2021 paper "Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features"

deep-gaussian-processes physics-informed-learning

Updated May 25, 2022
Python

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