pmorenoz / ContinualGPLinks
Continual Gaussian Processes
☆31Updated 2 years ago
Alternatives and similar repositories for ContinualGP
Users that are interested in ContinualGP are comparing it to the libraries listed below
Sorting:
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 6 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆71Updated last year
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆25Updated last year
- Stochastic variational heteroscedastic Gaussian process☆15Updated 6 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 years ago
- Streaming sparse Gaussian process approximations☆69Updated 3 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆34Updated 3 years ago
- Gaussian Processes for Sequential Data☆19Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆45Updated last year
- Recyclable Gaussian Processes☆11Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- ☆15Updated 2 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆24Updated 6 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Hierarchical Change-Point Detection☆14Updated 7 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- Variational Gaussian Process State-Space Models☆25Updated 10 years ago
- Code for Deep Structured Mixtures of Gaussian Processes (DSMGPs)☆11Updated 4 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆101Updated 6 years ago
- Library for Deep Gaussian Processes based on GPflow☆18Updated 5 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆128Updated last year
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆66Updated 6 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆34Updated 8 years ago