andymiller / vboost
code supplement for variational boosting (https://arxiv.org/abs/1611.06585)
☆11Updated 7 years ago
Alternatives and similar repositories for vboost
Users that are interested in vboost are comparing it to the libraries listed below
Sorting:
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- ☆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 repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆84Updated 4 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- ☆28Updated 6 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
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- Experiments for the Neural Autoregressive Flows paper☆124Updated 3 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- ☆26Updated 7 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 6 years ago
- Various estimators of the infinite dimensional exponential family model☆15Updated 8 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago