lewisKit / Amortized_SVGD
Experiments of amortized stein variational gradient
☆16Updated 7 years ago
Related projects: ⓘ
- ☆39Updated 5 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆62Updated 6 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆31Updated 4 years ago
- Repo for a paper about constructing priors on very deep models.☆69Updated 8 years ago
- Gaussian Processes in Pytorch☆74Updated 4 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 7 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 6 years ago
- Variational Fourier Features☆81Updated 3 years ago
- ☆25Updated 6 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆106Updated 6 years ago
- Neural Processes implementation for 1D regression☆65Updated 5 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆38Updated 3 years ago
- Various estimators of the infinite dimensional exponential family model☆15Updated 7 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆63Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆64Updated 4 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆66Updated 5 years ago
- A Python implementation of the gradient REBAR estimator.☆45Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆43Updated 6 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆47Updated 8 years ago
- A generic Monte Carlo method based on the Gumbel-Max trick.☆32Updated 8 years ago
- Natural Gradient, Variational Inference☆28Updated 4 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- An extension to Sacred for automated hyperparameter optimization.☆59Updated 6 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆145Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- ☆37Updated 5 years ago