AlexTMallen / koopman-forecasting
Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory
☆36Updated 3 years ago
Alternatives and similar repositories for koopman-forecasting
Users that are interested in koopman-forecasting are comparing it to the libraries listed below
Sorting:
- Deep Probabilistic Koopman: long-term time-series forecasting under quasi-periodic uncertainty☆23Updated 3 years ago
- State-space deep Gaussian processes in Python and Matlab☆30Updated 2 years ago
- ☆32Updated last year
- ☆29Updated 2 years ago
- ☆21Updated 4 years ago
- Dynamic mode decomposition with dependent structure among observables (Graph DMD)☆13Updated 5 years ago
- How to train a neural ODE for time series/weather forecasting☆38Updated 2 years ago
- Implementation of a reservoir computer with functions to optimize the parameters and calculate the Lyapunov exponents☆30Updated 3 years ago
- Consistent Koopman Autoencoders☆74Updated last year
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- ☆14Updated last year
- Linear and non-linear spectral forecasting algorithms☆137Updated 4 years ago
- Scalable Gaussian Process Regression with Derivatives☆38Updated 6 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆55Updated 2 years ago
- ☆21Updated 2 years ago
- ☆20Updated 6 years ago
- ☆30Updated 2 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- ☆11Updated 4 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆29Updated 2 years ago
- ☆29Updated 6 years ago
- Code for Copula conformal prediction paper (ICLR 2024)☆29Updated 7 months ago
- Port-Hamiltonian Approach to Neural Network Training☆24Updated 5 years ago
- Benchmark for learning stiff problems using physics-informed machine learning☆11Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆25Updated 3 years ago
- a collection of modern sparse (regularized) linear regression algorithms.☆61Updated 5 years ago
- code for "Neural Jump Ordinary Differential Equations"☆30Updated 2 years ago
- Bayesian Adaptive Spline Surfaces for flexible and automatic regression☆24Updated 10 months ago