andymiller / vboost
code supplement for variational boosting (https://arxiv.org/abs/1611.06585)
☆11Updated 7 years ago
Related projects ⓘ
Alternatives and complementary repositories for vboost
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Gaussian Processes for Sequential Data☆18Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆23Updated 5 years ago
- ☆40Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 6 years ago
- ☆28Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆109Updated 2 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆147Updated 5 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆28Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆24Updated 6 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 6 years ago
- Black box variational inference for state space models☆1Updated 8 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 3 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 3 years ago
- customized GPflow with simple Tensorflow API☆17Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated last month
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 4 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 7 years ago
- Variational Autoencoders with Normalizing Flows☆9Updated 6 years ago
- Additive Gaussian Process Bandits - version 1.0☆25Updated 7 years ago