cagatayyildiz / npdeLinks
Nonparametric Differential Equation Modeling
☆56Updated last year
Alternatives and similar repositories for npde
Users that are interested in npde are comparing it to the libraries listed below
Sorting:
- Learning unknown ODE models with Gaussian processes☆27Updated 7 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- ☆28Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆64Updated 4 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- ☆112Updated 4 years ago
- Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)☆11Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 10 months ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆24Updated 6 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆45Updated 7 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆55Updated 4 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- Library for Bayesian Quadrature☆32Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- Data-driven dynamical systems toolbox.☆78Updated last month
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Refining continuous-in-depth neural networks☆42Updated 4 years ago
- ☆30Updated 3 years ago
- Gaussian Processes for Sequential Data☆19Updated 4 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- ☆15Updated 2 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆47Updated 4 years ago
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated 2 years ago
- Scalable Gaussian Process Regression with Derivatives☆38Updated 6 years ago