blei-lab / variational-smcLinks
Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
☆65Updated 6 years ago
Alternatives and similar repositories for variational-smc
Users that are interested in variational-smc are comparing it to the libraries listed below
Sorting:
- ☆40Updated 6 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- Tree-structured recurrent switching linear dynamical systems☆36Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Python implementation of the PR-SSM.☆51Updated 7 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- ☆29Updated 6 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Variational Fourier Features☆85Updated 4 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆39Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 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