wwangdg's Stars
stnamjef/SPINN
Source code for Separable PINN
WillDreamer/Awesome-AI4CFD
Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey
tancik/fourier-feature-networks
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
pauloacs/DLpisoFoam
Machine Learning enhanced CFD solver for incompressible isothermal fluid flow
bitzhangcy/Neural-PDE-Solver
ShotaDeguchi/PINN_TF2
Implementation of PINNs in TensorFlow 2
szagoruyko/pytorchviz
A small package to create visualizations of PyTorch execution graphs
pratikrathore8/opt_for_pinns
HarborLibrary/Political-Science
政治
PredictiveIntelligenceLab/jaxpi
i207M/PINNacle
Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
Boris-73-TA/OrthogPolyKANs
Kolmogorov-Arnold Networks (KAN) using orthogonal polynomials instead of B-splines.
mintisan/awesome-kan
A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.
SynodicMonth/ChebyKAN
Kolmogorov-Arnold Networks (KAN) using Chebyshev polynomials instead of B-splines.
1ssb/torchkan
An easy to use PyTorch implementation of the Kolmogorov Arnold Network and a few novel variations
SpaceLearner/JacobiKAN
Kolmogorov-Arnold Networks (KAN) using Jacobi polynomials instead of B-splines.
rezaakb/pinns-jax
PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.
schrodingercatss/tuning_playbook_zh_cn
一本系统地教你将深度学习模型的性能最大化的战术手册。
KindXiaoming/pykan
Kolmogorov Arnold Networks
frgfm/torch-cam
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
comp-physics/CPINN
Competitive Physics Informed Networks
huangyi89/IB-PINN
aaronbuhendwa/twophasePINN
Physics-informed neural networks for two-phase flow problems
Weishuo93/NN_Pred
An interfacing library to deploy machine-learning models in CFD codes easily
tumaer/JAXFLUIDS
Differentiable Fluid Dynamics Package
akasharidas/subprecision-cfd
Code for "Deep neural networks to correct sub-precision errors in CFD"
BaratiLab/Diffusion-based-Fluid-Super-resolution
PyTorch implementation of the diffusion-based method for CFD data super-resolution proposed in the paper "A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction".
IllinoisRocstar/AccelerateCFD_CE
Community Edition of AccelerateCFD platform for creating reduced order models from high fidelity CFD