wjmaddox / online_gpLinks
Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
☆64Updated 4 years ago
Alternatives and similar repositories for online_gp
Users that are interested in online_gp are comparing it to the libraries listed below
Sorting:
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Online variational GPs☆37Updated 2 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- Streaming sparse Gaussian process approximations☆69Updated 3 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 10 months ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆33Updated 2 years ago
- Scalable Gaussian Process Regression with Derivatives☆38Updated 7 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆54Updated 4 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆34Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆27Updated last year
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- ☆155Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Pre-trained Gaussian processes for Bayesian optimization☆99Updated 8 months ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Max-value Entropy Search for Efficient Bayesian Optimization☆80Updated 3 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- A curated list of resources for learning Gaussian Processes☆40Updated 4 years ago
- Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds☆26Updated last year
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 3 years ago
- ☆112Updated 4 years ago