NN
A resource for learning about Machine learning & Deep Learning
Deep Learning for Reduced Order Modelling
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.
VIP cheatsheets for Stanford's CS 230 Deep Learning
The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-uniform parameter/time-varying grid, such that the Kolmogoro…
This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means of neural networks using TensorFlow.
A library for scientific machine learning and physics-informed learning
Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
Time-series learning of latent-space dynamics for reduced-order model closure
A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269
Python implementation of uplifted reduced order modeling (UROM) framework
Non-intrusive surrogate modeling for parametrized time-dependent partial differential equations using convolutional autoencoders
A compilation of examples, primarily for testing DMD-based methods.
Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh Bénard convection
A brief tutorial on the Wasserstein auto-encoder
A Collection of Variational Autoencoders (VAE) in PyTorch.
I have created this repository to share my code for 2D numerical solving of Navier stokes equations (incompressible flow); although it will take a little time for me to completely update the repos…
This repository contains implementations and illustrative code to accompany DeepMind publications
Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.
Temporal Fusion Transformers for Tensorflow 2.x