snagcliffs / RKNNLinks
☆21Updated 7 years ago
Alternatives and similar repositories for RKNN
Users that are interested in RKNN are comparing it to the libraries listed below
Sorting:
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆156Updated 5 years ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆26Updated 3 years ago
- Linear and non-linear spectral forecasting algorithms☆137Updated 4 years ago
- A pyTorch Extension for Applied Mathematics☆40Updated 5 years ago
- RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical sy…☆96Updated 2 years ago
- Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory☆35Updated 3 years ago
- SINDy (Sparse Identification of Nonlinear Dynamics) algorithms☆79Updated 2 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Dynamic Mode Decomposition☆60Updated 8 years ago
- ☆11Updated 7 years ago
- Python package for calculating fractional derivatives.☆59Updated last year
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆44Updated 3 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 years ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Koopman Mode Decomposition☆73Updated 8 years ago
- Parametric Gaussian Process Regression for Big Data (Matlab Version)☆24Updated 7 years ago
- ☆41Updated 7 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- ☆15Updated 2 years ago
- Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…☆21Updated 2 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
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆59Updated 4 years ago
- ☆73Updated 5 years ago
- a collection of modern sparse (regularized) linear regression algorithms.☆65Updated 5 years ago
- Deep Learning application to the partial differential equations☆30Updated 7 years ago
- State-space deep Gaussian processes in Python and Matlab☆30Updated 3 years ago