yorkerlin / VB-MixEF
Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
☆17Updated 3 years ago
Related projects: ⓘ
- Python and MATLAB code for Stein Variational sampling methods☆23Updated 5 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆27Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆63Updated 5 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆19Updated 4 years ago
- Code for Fast Information-theoretic Bayesian Optimisation☆16Updated 6 years ago
- Code for density estimation with nonparametric cluster shapes.☆38Updated 8 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆21Updated 7 years ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆25Updated 10 years ago
- Codes for Hilbert space reduced-rank GP regression☆11Updated 5 years ago
- ☆11Updated 8 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 8 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆43Updated 6 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 9 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Variational Gaussian Process State-Space Models☆21Updated 8 years ago
- Recyclable Gaussian Processes☆11Updated last year
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆26Updated 3 years ago
- code supplement for variational boosting (https://arxiv.org/abs/1611.06585)☆11Updated 7 years ago
- Nonparametric Differential Equation Modeling☆50Updated 6 months ago
- Implementation of the PAC Bayesian GP learning method.☆10Updated 5 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆28Updated last year
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 7 months ago
- Stochastic Gradient Riemannian Langevin Dynamics☆32Updated 9 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 5 years ago
- FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"☆29Updated 3 years ago
- Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)☆18Updated 6 years ago