karlnapf / kernel_exp_family
Various estimators of the infinite dimensional exponential family model
☆15Updated 8 years ago
Alternatives and similar repositories for kernel_exp_family
Users that are interested in kernel_exp_family are comparing it to the libraries listed below
Sorting:
- ☆40Updated 6 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 6 years ago
- ☆28Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆84Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 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
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 5 years ago
- code release for the NIPS 2016 paper☆27Updated 8 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Variational Fourier Features☆84Updated 3 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 8 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 5 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- ☆26Updated 7 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 5 years ago