thangbui / deepGP_approxEPLinks
see https://github.com/thangbui/geepee for a faster implementation
☆37Updated 8 years ago
Alternatives and similar repositories for deepGP_approxEP
Users that are interested in deepGP_approxEP are comparing it to the libraries listed below
Sorting:
- ☆40Updated 6 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- ☆28Updated 6 years ago
- Additive Gaussian Process Bandits - version 1.0☆27Updated 8 years ago
- Deep Gaussian Processes in matlab☆93Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Variational Fourier Features☆86Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago