sparseMCMC / NIPS2015Links
☆12Updated 10 years ago
Alternatives and similar repositories for NIPS2015
Users that are interested in NIPS2015 are comparing it to the libraries listed below
Sorting:
- Bayesian Nonparametric Mixture Models in Julia☆14Updated 8 years ago
- Variational Sparse Spectrum Gaussian Process toolkit☆22Updated 10 years ago
- Preconditioning Kernel Matrices☆15Updated 9 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Updated 7 years ago
- Black Box Variational Inference☆14Updated 10 years ago
- Jax-based MaxEnt☆17Updated 6 years ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆29Updated 7 years ago
- Expectation Particle Belief Propagation code☆12Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆66Updated 6 years ago
- Structure learning for sparse graphs with latent variables☆45Updated 9 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.☆36Updated 11 years ago
- Recognizing and exploiting conjugacy without a domain-specific language☆36Updated 6 years ago
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 8 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Matlab code implementing Minimum Probability Flow Learning.☆69Updated 11 years ago
- Nonlinear Information Bottleneck☆54Updated 3 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Automatic Reparameterisation of Probabilistic Programs☆36Updated 5 years ago
- This repository houses the code for the community website http://www.probabilistic-numerics.org☆36Updated 5 years ago
- code supplement for variational boosting (https://arxiv.org/abs/1611.06585)☆11Updated 8 years ago
- Practical tools for quantifying how well a sample approximates a target distribution☆28Updated 5 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 5 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Julia package for Bayesian mixture models☆28Updated 5 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆19Updated 5 years ago
- Gaussian Processes for Sequential Data☆19Updated 5 years ago
- Stochastic Gradient MCMC algorithms implemented in theano (and autograd)☆10Updated 9 years ago