Alternatives and similar repositories for ml:

Users that are interested in ml are comparing it to the libraries listed below

• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆58Updated 7 months ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆46Updated last year
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆64Updated 5 years ago
• hichamjanati / mutar
  Multi-task regression in Python
  ☆26Updated 4 years ago
• slinderman / stats305c
  STATS305C: Applied Statistics III (Spring, 2023)
  ☆23Updated last year
• StannisZhou / mixed_hmc
  ☆12Updated 3 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆62Updated 3 weeks ago
• benchopt / template_benchmark
  ☆25Updated 3 weeks ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆39Updated 5 years ago
• sbi-dev / pyknos
  Conditional density estimation with neural networks
  ☆30Updated 3 weeks ago
• acerbilab / pyvbmc
  PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
  ☆117Updated 2 weeks ago
• karlnapf / ds3_kernel_testing
  Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"
  ☆26Updated 6 years ago
• sphinxteam / DukeLecture2018
  Set of Lecture at Duke in 2018 by Lenka Zdeborova and Florent Krzakala "Statistical Physics For Optimization and Learning"
  ☆16Updated 5 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆60Updated 7 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 6 months ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆98Updated last year
• pierrebaudot / infotopopy
  computes most of information functions (joint entropy, conditional, mutual information, total correlation information distance) and deep …
  ☆36Updated 2 years ago
• slinderman / stats271sp2021
  Material for STATS271: Applied Bayesian Statistics (Spring 2021)
  ☆26Updated 3 years ago
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 4 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆100Updated last year
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆36Updated 4 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• gpschool / gpss20
  Gaussian Process and Uncertainty Quantification Summer School 2020
  ☆33Updated 2 years ago
• blackjax-devs / sampling-book
  Tutorials and sampling algorithm comparisons
  ☆70Updated this week
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• earcher / vilds
  Black box variational inference for state space models
  ☆1Updated 8 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 4 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• probml / JSL
  Jax SSM Library
  ☆49Updated 2 years ago
• gatsby-sahani / gp-sde
  ☆13Updated last year