gwgundersen / ml
A didactic Python library with well-commented and annotated implementations of machine learning algorithms.
☆53Updated 4 years ago
Alternatives and similar repositories for ml:
Users that are interested in ml are comparing it to the libraries listed below
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 10 months ago
- PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python☆117Updated 2 months ago
- Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead☆73Updated 4 years ago
- Material for STATS271: Applied Bayesian Statistics (Spring 2021)☆26Updated 3 years ago
- STATS305C: Applied Statistics III (Spring, 2023)☆25Updated last year
- Implementation of the Gaussian Process Autoregressive Regression Model☆65Updated 3 months ago
- Hidden Markov models in PyMC3☆99Updated last year
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Dynamical Components Analysis☆32Updated last year
- A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-conve…☆56Updated 2 years ago
- Black box variational inference for state space models☆1Updated 8 years ago
- An ongoing collection of ipython notebooks on neuroscience from xcorr: computational neuroscience.☆78Updated 2 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆103Updated last year
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- computes most of information functions (joint entropy, conditional, mutual information, total correlation information distance) and deep …☆37Updated 3 years ago
- Sequential Neural Likelihood☆41Updated 5 years ago
- Materials of the Nordic Probabilistic AI School 2019.☆129Updated 4 years ago
- ☆94Updated 6 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 4 years ago
- Conditional density estimation with neural networks☆30Updated 3 months ago
- ICML 2017. Kernel-based adaptive linear-time independence test.☆16Updated 3 years ago
- Tutorials and sampling algorithm comparisons☆74Updated this week
- Utilities for probabilistic ML☆34Updated last year
- Bayesian Regression Models in Pyro☆71Updated 8 months ago
- ☆17Updated 2 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- Bayesian Bandits☆68Updated last year
- Gaussian Process and Uncertainty Quantification Summer School 2020☆33Updated 2 years ago