sisl / deep_flow_control
Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
☆46Updated 6 years ago
Alternatives and similar repositories for deep_flow_control:
Users that are interested in deep_flow_control are comparing it to the libraries listed below
- ☆62Updated 5 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆55Updated 4 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 4 years ago
- Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition☆40Updated 3 years ago
- Shallow Learning for Flow Reconstruction with Limited Sensors and Limited Data☆37Updated 6 years ago
- ☆41Updated 4 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☆48Updated 4 years ago
- Repository from the paper https://arxiv.org/abs/1908.04127, to train Deep Reinforcement Learning in Fluid Mechanics Setup.☆63Updated 3 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆106Updated 4 years ago
- ☆120Updated last year
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆67Updated 4 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆29Updated 2 years ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆19Updated 2 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆28Updated 2 years ago
- PyTorch-FEniCS interface☆99Updated 3 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆41Updated 6 years ago
- ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis☆51Updated last year
- Code for the ICLR 2020 paper "Learning to Control PDEs"☆32Updated 4 years ago
- The code used, and a docker image to run it, of the paper `Exploiting locality and physical invariants to design effective Deep Reinforce…☆13Updated 5 years ago
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Updated 4 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆91Updated 2 years ago
- reinforcement learning for active fluid control☆30Updated 4 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆24Updated 3 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆143Updated 5 years ago
- An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.☆62Updated last month
- Multi Fidelity Monte Carlo☆25Updated 5 years ago
- Deep Learning application to the partial differential equations☆30Updated 6 years ago