wesselb / gpar
Implementation of the Gaussian Process Autoregressive Regression Model
☆62Updated 3 years ago
Alternatives and similar repositories for gpar:
Users that are interested in gpar are comparing it to the libraries listed below
- Light-weighted code for Orthogonal Additive Gaussian Processes☆40Updated 5 months ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆32Updated 2 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 7 months ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆21Updated 5 years ago
- Conditional density estimation with neural networks☆29Updated 4 months ago
- ☆13Updated last year
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Fully nonstationary, heteroscedastic GP for Matlab☆14Updated 5 months ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆29Updated 6 months ago
- Collection of resources from each meetup event☆13Updated 4 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 4 years ago
- ☆28Updated 5 years ago
- Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead☆73Updated 4 years ago
- Heterogeneous Multi-output Gaussian Processes☆51Updated 4 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆68Updated 4 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆122Updated 3 months ago
- A collection of Gaussian process models☆30Updated 7 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 11 months ago
- Continual Gaussian Processes☆32Updated last year
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆232Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆99Updated last year
- Gaussian Processes for Sequential Data☆18Updated 4 years ago