wesselb / gparLinks
Implementation of the Gaussian Process Autoregressive Regression Model
☆68Updated 10 months ago
Alternatives and similar repositories for gpar
Users that are interested in gpar are comparing it to the libraries listed below
Sorting:
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Codes for Hilbert space reduced-rank GP regression☆14Updated 6 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- Gaussian process modelling in Python☆225Updated 11 months ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆13Updated last year
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- Continual Gaussian Processes☆31Updated 2 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆45Updated 7 years ago
- Sequential Neural Likelihood☆42Updated 6 years ago
- ☆15Updated 2 years ago
- ABCpy package☆116Updated last year
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆34Updated 8 years ago
- Manifold Markov chain Monte Carlo methods in Python☆236Updated last week
- ☆155Updated 3 years ago
- A Python toolkit for (simulation-based) inference and the mechanization of science.☆53Updated 3 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
- A collection of Gaussian process models☆30Updated 8 years ago
- PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python☆121Updated this week
- Finding the conditional distributions of a Gaussian Mixture Model☆12Updated 6 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago