hegdepashupati / gaussian-process-odesLinks
Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
☆12Updated 3 years ago
Alternatives and similar repositories for gaussian-process-odes
Users that are interested in gaussian-process-odes are comparing it to the libraries listed below
Sorting:
- A Python package to learn the Koopman operator.☆60Updated 8 months ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 3 months ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆64Updated 4 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆53Updated last year
- Code for "Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference" (ICML 2024)☆22Updated 2 months ago
- Kernel Identification Through Transformers☆13Updated 2 years ago
- Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"☆13Updated 5 months ago
- Data-driven dynamical systems toolbox.☆74Updated last week
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆29Updated last year
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆49Updated 2 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 7 years ago
- ☆29Updated 2 years ago
- Differentiable Principal Component Analysis (PCA) implementation in JAX☆29Updated 3 months ago
- Riemannian Optimization Using JAX☆51Updated last year
- ☆52Updated 2 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 2 years ago
- Offline Contextual Bayesian Optimization☆14Updated 2 years ago
- Library for Bayesian Quadrature☆32Updated 6 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆34Updated 3 years ago
- A framework for neural network control of dynamical systems over graphs.☆57Updated 2 years ago
- Pre-trained Gaussian processes for Bayesian optimization☆94Updated 3 months ago
- Code for Gaussian Score Matching Variational Inference☆34Updated 5 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆112Updated 4 months ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 6 months ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Stochastic Normalizing Flows☆78Updated 3 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆56Updated 3 years ago