mackelab / autohmmLinks
Hidden Markov Models (HMMs) with tied states and autoregressive observations
☆23Updated 5 years ago
Alternatives and similar repositories for autohmm
Users that are interested in autohmm are comparing it to the libraries listed below
Sorting:
- Generalized linear models for neural spike train modeling, in Python! With GPU-accelerated fully-Bayesian inference, MAP inference, and n…☆45Updated 10 years ago
- My PhD Thesis☆22Updated 9 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- ☆155Updated 6 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆83Updated 5 years ago
- Tree-structured recurrent switching linear dynamical systems☆37Updated 5 years ago
- Bayesian GPLVM in MATLAB and R☆75Updated 8 years ago
- A collection of Gaussian process models☆30Updated 8 years ago
- Backpropagate derivatives through the Cholesky decomposition☆58Updated 5 years ago
- autoregressive plugin☆27Updated 2 years ago
- Variational Fourier Features☆85Updated 4 years ago
- An ongoing collection of ipython notebooks on neuroscience from xcorr: computational neuroscience.☆78Updated 3 years ago
- Clustering time series using Gaussian processes and Variational Bayes.☆39Updated 5 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 11 years ago
- ☆98Updated 7 years ago
- Keras for Science☆72Updated 7 years ago
- 🕝 Time-warped principal components analysis (twPCA)☆127Updated 4 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Library of common tools for machine learning research.☆41Updated 7 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago
- Structured Machine Learning in Python☆46Updated 2 years ago
- This code accompanies the proximity variational inference paper.☆18Updated 6 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 8 years ago
- A collection of IPython notebooks from a graduate-level statistics course run by Tom Wallis and Philipp Berens☆27Updated 10 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- ☆99Updated 7 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 7 years ago
- Collapsed Variational Bayes☆72Updated 6 years ago
- Bayesian Effective Connectivity☆54Updated 6 years ago
- Implementation of Hidden Markov Models in pymc3☆62Updated 8 years ago