xdfeng7370

Deep-Ritz-Method

Reproduce the first two numerical experiments(Pytorch)

Multi-fidelity-neural-network-

PINNs

PyTorch Implementation of Physics-informed Neural Networks

pyapprox

pymc

Bayesian Modeling and Probabilistic Programming in Python

shenfun

High performance computational platform in Python for the spectral Galerkin method

uncertainty-toolbox

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

xdfeng7370/Multi-fidelity-neural-network-

xdfeng7370/Deep-Ritz-Method

Reproduce the first two numerical experiments(Pytorch)

xdfeng7370/Some-numerical-experiments-on-DRm-DGM-and-WAN

I reproduce three simple PDE based on Pytorch , including irregular domain and non-smooth function. In first two examples, I test deep ritz method and PINNs. In the last examples, I test WAN method (weak adversarial networks).

xdfeng7370/multiscale_hw

Multiscale homework

xdfeng7370/gradient-flow-in-pinns

Depict the gradient information in pinns

xdfeng7370/PINNs

PyTorch Implementation of Physics-informed Neural Networks

xdfeng7370/pyapprox

xdfeng7370/pymc

Bayesian Modeling and Probabilistic Programming in Python

xdfeng7370/shenfun

High performance computational platform in Python for the spectral Galerkin method

xdfeng7370/some_tricks_in_deep_learning

I reproduce three numerical experiments. The first example depicts the symmetric structure in neural network; the second example shows the adaptive activation function, namely, $\sigma(x)\to \sigma(ax)$, where $a$ is a learnable parameter. The last example shows the spectral bias in the DNN.

xdfeng7370/uncertainty-toolbox

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

xdfeng7370/xdfeng7370.github.io