FrancescoRegazzoni / LDNetsLinks
☆63Updated last year
Alternatives and similar repositories for LDNets
Users that are interested in LDNets are comparing it to the libraries listed below
Sorting:
- The public repository about our joint FINN research project☆38Updated 3 years ago
- A library for dimensionality reduction on spatial-temporal PDE☆71Updated last month
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆37Updated 2 months ago
- Pseudospectral Kolmogorov Flow Solver☆42Updated 2 years ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆106Updated last year
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 11 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Updated 5 years ago
- ☆50Updated 2 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆47Updated 3 weeks ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆58Updated last year
- Turbulent flow network source code☆71Updated 10 months ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆20Updated 3 years ago
- Transformers for modeling physical systems☆148Updated 2 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆62Updated 5 years ago
- Multi-fidelity reduced-order surrogate modeling☆31Updated 7 months ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆36Updated 4 years ago
- Example problems in Physics informed neural network in JAX☆81Updated 2 years ago
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆24Updated 3 years ago
- Code for the paper "Generative AI for fast and accurate statistical computation of fluids"☆48Updated 6 months ago
- Enhancing Dynamic Mode Decomposition using Autoencoder Networks.☆35Updated 4 years ago
- ☆118Updated 6 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆52Updated 3 years ago
- mathLab mirror of Python Dynamic Mode Decomposition☆113Updated 11 months ago
- ☆29Updated last year
- ☆54Updated 3 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆76Updated 9 months ago
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems☆40Updated 11 months ago
- ☆110Updated 4 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆43Updated 3 years ago