amkatrutsa / DeepPDELinks
Deep Learning application to the partial differential equations
☆30Updated 7 years ago
Alternatives and similar repositories for DeepPDE
Users that are interested in DeepPDE are comparing it to the libraries listed below
Sorting:
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Machine learning of linear differential equations using Gaussian processes☆24Updated 7 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 5 years ago
- A Discussion on Solving Partial Differential Equations using Neural Networks☆66Updated 5 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- ☆63Updated 5 years ago
- Deep Learning of Turbulent Scalar Mixing☆17Updated 5 years ago
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆48Updated 6 years ago
- CS230 Project: Deep Learning for PDE☆41Updated 6 years ago
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆19Updated 4 years ago
- Multi Fidelity Monte Carlo☆25Updated 5 years ago
- ☆41Updated 5 years ago
- Tutorial on a number of topics in Deep Learning☆35Updated 5 years ago
- jupyter notebooks for the neural nets and differential equation paper☆28Updated 4 years ago
- Shallow Learning for Flow Reconstruction with Limited Sensors and Limited Data☆37Updated 6 years ago
- Dynamic Mode Decomposition☆59Updated 7 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆43Updated 7 years ago
- ☆24Updated 6 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆115Updated 3 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆56Updated 4 years ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- UNIVR PDE course project and just for fun☆117Updated 8 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 4 years ago
- PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential op…☆26Updated last year
- Parametric Gaussian Process Regression for Big Data (Matlab Version)☆24Updated 7 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆92Updated 3 years ago
- Code for the ICLR 2020 paper "Learning to Control PDEs"☆33Updated 5 years ago