lewisKit / Amortized_SVGDLinks
Experiments of amortized stein variational gradient
☆16Updated 8 years ago
Alternatives and similar repositories for Amortized_SVGD
Users that are interested in Amortized_SVGD are comparing it to the libraries listed below
Sorting:
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 7 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆39Updated 4 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- ☆40Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- ☆26Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆182Updated 6 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Reweighted Expectation Maximization☆29Updated 6 years ago
- A generic Monte Carlo method based on the Gumbel-Max trick.☆32Updated 9 years ago
- Variational Fourier Features☆86Updated 4 years ago
- ☆37Updated 5 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Updated 9 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- code for stochastic expectation propagation☆16Updated 9 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆125Updated 6 years ago