cics-nd / cnn-surrogateLinks
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
☆107Updated 5 years ago
Alternatives and similar repositories for cnn-surrogate
Users that are interested in cnn-surrogate are comparing it to the libraries listed below
Sorting:
- ☆63Updated 6 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆150Updated 6 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Updated 5 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆94Updated 2 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆149Updated 5 years ago
- ☆26Updated 7 years ago
- Multi-fidelity Generative Deep Learning Turbulent Flows☆37Updated 5 years ago
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆49Updated 7 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆42Updated 5 years ago
- A pyTorch Extension for Applied Mathematics☆40Updated 5 years ago
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆284Updated 3 years ago
- ☆118Updated 6 years ago
- ☆50Updated 2 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆62Updated 5 years ago
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆70Updated 9 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆70Updated 4 years ago
- Solving PDEs with NNs☆55Updated 3 years ago
- Code for "Learning data-driven discretizations for partial differential equations"☆167Updated 4 months ago
- ☆13Updated 6 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Deep Learning of Vortex Induced Vibrations☆99Updated 5 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 2 years ago
- POD-PINN code and manuscript☆57Updated last year
- ☆40Updated 2 years ago
- Machine learning of linear differential equations using Gaussian processes☆25Updated 7 years ago
- MeshfreeFlowNet: Physical Constrained Space Time Super-Resolution☆108Updated 4 years ago