PhIMaL / DeePyMoDLinks
☆48Updated last year
Alternatives and similar repositories for DeePyMoD
Users that are interested in DeePyMoD are comparing it to the libraries listed below
Sorting:
- A library for dimensionality reduction on spatial-temporal PDE☆66Updated last year
- The public repository about our joint FINN research project☆38Updated 2 years ago
- ☆116Updated 6 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆35Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Applications of PINOs☆132Updated 2 years ago
- ☆99Updated 3 years ago
- ☆54Updated 2 years ago
- ☆36Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆51Updated 3 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…☆41Updated 2 years ago
- ☆42Updated 2 years ago
- Turbulent flow network source code☆70Updated 5 months ago
- Pseudospectral Kolmogorov Flow Solver☆40Updated last year
- ☆63Updated 6 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)☆16Updated 4 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 2 months ago
- ☆38Updated 2 years ago
- Physics-encoded recurrent convolutional neural network☆46Updated 3 years ago
- ☆13Updated 5 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆32Updated last year
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems☆35Updated 5 months ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆67Updated 4 months ago
- Characterizing possible failure modes in physics-informed neural networks.☆138Updated 3 years ago
- ☆187Updated 4 months ago
- Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …☆33Updated 4 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆150Updated 5 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago