snagcliffs / RKNNLinks
☆20Updated 7 years ago
Alternatives and similar repositories for RKNN
Users that are interested in RKNN are comparing it to the libraries listed below
Sorting:
- RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical sy…☆95Updated 2 years ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆154Updated 5 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 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
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- Linear and non-linear spectral forecasting algorithms☆137Updated 4 years ago
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆43Updated 2 years ago
- ☆11Updated 7 years ago
- Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory☆35Updated 3 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- SINDy (Sparse Identification of Nonlinear Dynamics) algorithms☆78Updated 2 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 5 years ago
- ☆41Updated 7 years ago
- Dynamic Mode Decomposition☆59Updated 8 years ago
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆49Updated 6 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- ☆72Updated 4 years ago
- Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …☆33Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 3 years ago
- Use SINDY algorithm to discover a dynamical system from coronavirus data☆13Updated last year
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Python package for calculating fractional derivatives.☆57Updated 11 months 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
- Gaussian processes regression models with linear inequality constraints☆15Updated last year
- Supporting material for Princeton ORF522☆13Updated 8 months ago
- Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition☆40Updated 3 years ago
- Koopman Mode Decomposition☆72Updated 8 years ago
- a collection of modern sparse (regularized) linear regression algorithms.☆64Updated 5 years ago