DanielTakeshi / MCMC_and_Dynamics
Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
☆42Updated 5 years ago
Alternatives and similar repositories for MCMC_and_Dynamics:
Users that are interested in MCMC_and_Dynamics are comparing it to the libraries listed below
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- ☆25Updated 2 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆47Updated 9 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 8 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- ☆28Updated 5 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆59Updated 4 years ago
- ☆59Updated 6 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago