jamesross2 / Bayesian-HMM
A non-parametric Bayesian approach to Hidden Markov Models
☆87Updated last year
Alternatives and similar repositories for Bayesian-HMM:
Users that are interested in Bayesian-HMM are comparing it to the libraries listed below
- Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model☆28Updated 4 years ago
- ☆94Updated 6 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- some tools for gaussian linear dynamical systems☆89Updated 6 years ago
- Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…☆77Updated last year
- Python package for canonical vine copula trees with mixed continuous and discrete marginals☆47Updated last year
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 2 years ago
- Input Output Hidden Markov Model (IOHMM) in Python☆165Updated 10 months ago
- REGAIN (Regularised Graphical Inference)☆29Updated last year
- Implementation of the Gaussian Process Autoregressive Regression Model☆65Updated 3 months ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Continual Gaussian Processes☆32Updated last year
- A library for hidden semi-Markov models with explicit durations☆84Updated 3 years ago
- Code for Hidden Markov Nonlinear ICA☆24Updated 3 years ago
- Recurrent state-space models for decision making☆30Updated 2 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 10 months ago
- Black box variational inference for state space models☆1Updated 8 years ago
- autoregressive plugin☆27Updated 2 years ago
- ☆14Updated last year
- Tree-structured recurrent switching linear dynamical systems☆36Updated 4 years ago
- Implementation of Hidden Markov Models in pymc3☆61Updated 8 years ago
- Gaussian process regression + automatical model selection for logitudinal -omics data☆21Updated 4 years ago
- Convergent Cross Mapping in Scikit Learn's style☆98Updated 4 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 4 years ago
- Variational Gaussian Process State-Space Models☆23Updated 9 years ago
- Fastfit matlab toolbox☆27Updated 8 years ago
- Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead☆73Updated 4 years ago
- ☆155Updated 5 years ago
- PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python☆117Updated 2 months ago
- Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…☆78Updated 7 years ago