Pinned Repositories
A-PINN
A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations
AMAW-PINN
Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting
CFDPython
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
easyPDE
偏微分方程的有限元方法
HNS
IAM-IOTB
指令驱动模型
IOM-RBF-FD
Iterative optimization method for determining optimal shape parameter in RBF-FD
MultiscalePINNs
Neural-PDE-Solver
PDEcollector
Collect PDE and its true solution
hsbhc's Repositories
hsbhc/AMAW-PINN
Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting
hsbhc/IAM-IOTB
指令驱动模型
hsbhc/easyPDE
偏微分方程的有限元方法
hsbhc/PDEcollector
Collect PDE and its true solution
hsbhc/HNS
hsbhc/IOM-RBF-FD
Iterative optimization method for determining optimal shape parameter in RBF-FD
hsbhc/A-PINN
A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations
hsbhc/CFDPython
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
hsbhc/MultiscalePINNs
hsbhc/Neural-PDE-Solver
hsbhc/PDEBench
PDEBench: An Extensive Benchmark for Scientific Machine Learning
hsbhc/Physics-informed-DeepONets
hsbhc/Physics-Informed-Neural-Networks
Investigating PINNs
hsbhc/PINN-elastodynamics
physics-informed neural network for elastodynamics problem
hsbhc/PINN-laminar-flow
Physics-informed neural network for solving fluid dynamics problems
hsbhc/SA-PINNs
Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]