lawmurray / BirchLinks
A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.
☆118Updated 8 months ago
Alternatives and similar repositories for Birch
Users that are interested in Birch are comparing it to the libraries listed below
Sorting:
- Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt…☆120Updated last week
- Causal, Higher-Order, Probabilistic Programming☆174Updated last week
- Probabilistic Programming with Gaussian processes in Julia☆345Updated 6 months ago
- Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo i…☆104Updated 3 years ago
- Gaussian Process package based on data augmentation, sparsity and natural gradients☆137Updated last year
- Automated Bayesian model discovery for time series data☆83Updated this week
- Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.☆151Updated 2 years ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆28Updated 7 years ago
- Featherweight embedded probabilistic programming language and compositional inference programming library☆18Updated 5 years ago
- Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform…☆125Updated 2 months ago
- Probabilistic programming via source rewriting☆421Updated last year
- "Distributions" that might not add to one.☆397Updated 6 months ago
- Robust implementation for random-walk Metropolis-Hastings algorithms☆116Updated 2 months ago
- Probabilistic programming system for fast and exact symbolic inference☆82Updated last year
- Automatic differentiation of Distributions using Tracker, Zygote, ForwardDiff and ReverseDiff☆153Updated last month
- Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.☆251Updated 2 months ago
- Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.☆63Updated last year
- Why multiple dispatch lets you write composable code☆40Updated 5 years ago
- Bayesian state-space modelling on high-performance hardware, including multicore, GPUs and distributed clusters.☆102Updated 2 years ago
- Julia code for Probabilistic Machine Learning☆38Updated 5 years ago
- A Julia package to support conjugate prior distributions.☆48Updated 2 years ago
- Bayesian Networks for Julia☆229Updated 6 months ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- Experiments with variational autoencoders in Julia☆17Updated 6 years ago
- Implementation of normalising flows and constrained random variable transformations☆255Updated this week
- Implementations of the models from the Statistical Rethinking book with Turing.jl☆163Updated 2 years ago
- A light interface to serial and multi-threaded Sequential Monte Carlo☆32Updated 3 years ago
- Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms☆314Updated last week
- Abstract types and methods for Gaussian Processes.☆271Updated last month
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 5 years ago