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autodiff

automatic differentiation made easier for C++

cae_lstm_roms

Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"

deeponet

Learning nonlinear operators via DeepONet

dvae

Official implementation of Dynamical VAEs

eat_pytorch_in_20_days

Pytorch🍊🍉 is delicious, just eat it! 😋😋

ezyrb

Easy Reduced Basis method

fem-vs-pinns

garom

GAROM-Generative Adversarial Reduce Order Modelling

gca-rom

GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.

gd-vae

Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.

ibpm

Immersed Boundary Projection Method

kriging-and-ge-kriging-model-toolbox

Gradient-enhanced Kriging surrogate model

lando

Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)

localrom

matconvnet

MatConvNet: CNNs for MATLAB

neuraluq

pina

Physics-Informed Neural networks for Advanced modeling

pod-dl-rom

Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition. Available on doi.org/10.1016/j.cma.2021.114181.

polynomial-chaos-expansion-and-gradient-enhanced-polynomial-chaos-model

pytorch-vae

A Variational Autoencoder (VAE) implemented in PyTorch

rodeo

sdis

Rare event estimation with Sequential Directional Importance Sampling (SDIS)

stein-variational-gradient-descent

code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

support-vector-regression

vae_tutorial

Caffe code to accompany my Tutorial on Variational Autoencoders

variational-autoencoder

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

vde

Variational Autoencoder for Dimensionality Reduction of Time-Series