naesseth / nestedsmcLinks
Implementation of various algorithms in the Nested Sequential Monte Carlo family of methods.
☆14Updated 9 years ago
Alternatives and similar repositories for nestedsmc
Users that are interested in nestedsmc are comparing it to the libraries listed below
Sorting:
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- ☆12Updated 3 months ago
- A Bayesian latent tree model of high-dimensional heterogeneous data☆23Updated 7 years ago
- Perform bayesian distribution regression☆13Updated 7 years ago
- Implementation of an algorithm for Markov chain Monte Carlo with data subsampling☆32Updated 9 years ago
- A Python library for reinforcement learning using Bayesian approaches☆54Updated 10 years ago
- ☆12Updated 2 years ago
- ☆10Updated 7 years ago
- Basic probability manipulation routines for discrete variables☆29Updated 7 years ago
- Fast, principled L1-regularized loss minimization☆24Updated last year
- Software for learning sparse Bayesian networks☆43Updated 4 years ago
- Structure learning for sparse graphs with latent variables☆45Updated 8 years ago
- An implementation of the SuperLearner algorithm in Python based on scikit-learn.☆25Updated 11 years ago
- Python package for inference with Gaussian processes☆11Updated 10 years ago
- Automatic Reparameterisation of Probabilistic Programs☆36Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"☆28Updated 6 years ago
- Bayesian multi-tensor factorization methods, with side information☆29Updated 5 years ago
- This repository houses the code for the community website http://www.probabilistic-numerics.org☆35Updated 5 years ago
- Bayesian Poisson Tucker decomposition☆17Updated 8 years ago
- Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo☆52Updated 12 years ago
- Unbiased Markov chain Monte Carlo with couplings☆29Updated 2 years ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆28Updated 6 years ago
- Posterior Server☆15Updated 8 years ago
- Generalized lasso implementations☆46Updated 9 months ago
- Code for Kernel Adaptive Metropolis-Hastings☆33Updated 10 years ago
- ☆67Updated 7 years ago
- Modular Probabilistic Programming on MXNet☆104Updated 2 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆69Updated 7 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 7 years ago