paraklas / GPTutorialLinks
A hands-on tutorial on supervised learning with Gaussian processes
☆37Updated 6 years ago
Alternatives and similar repositories for GPTutorial
Users that are interested in GPTutorial 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
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 5 years ago
- ☆42Updated 5 years ago
- ☆63Updated 6 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Updated 5 years ago
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆71Updated 9 years ago
- A pyTorch Extension for Applied Mathematics☆40Updated 5 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆107Updated 5 years ago
- Machine learning of linear differential equations using Gaussian processes☆26Updated 7 years ago
- ☆118Updated 6 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆33Updated 2 years ago
- Convolutional Solvers for Partial Differential Equations☆27Updated 5 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆149Updated 5 years ago
- Tutorial on Gaussian Processes☆64Updated 5 years ago
- ☆15Updated 5 years ago
- Multi Fidelity Monte Carlo☆24Updated 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 3 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆117Updated 3 years ago
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆49Updated 7 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 Generative Deep Learning Turbulent Flows☆37Updated 5 years ago
- ☆26Updated 7 years ago
- ☆43Updated 8 years ago
- ☆21Updated 5 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆45Updated 7 years ago
- Deep Learning application to the partial differential equations☆30Updated 7 years ago
- Publication of Python code used to train ModalPINN☆11Updated 3 years ago
- ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis☆56Updated 2 years ago
- ☆10Updated 5 years ago