sremes / nonstationary-spectral-kernels
Implementation for Non-stationary Spectral Kernels (NIPS 2017)
☆20Updated 5 years ago
Alternatives and similar repositories for nonstationary-spectral-kernels:
Users that are interested in nonstationary-spectral-kernels are comparing it to the libraries listed below
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 8 months ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆65Updated 2 months ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 5 years ago
- Codes for Hilbert space reduced-rank GP regression☆14Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 5 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- ☆40Updated 5 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆31Updated 8 years ago
- Continual Gaussian Processes☆32Updated last year
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Time-varying Autoregression with Low Rank Tensors☆15Updated 3 years ago
- ☆28Updated 6 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Sequential Neural Likelihood☆41Updated 5 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆26Updated 10 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆37Updated 3 years ago