cavaunpeu / random-effects-neural-networks

Related projects: ⓘ

• JackCaster / Intro_to_PyMC3
  Short introduction to Bayesian statistical modelling with PyMC3
  ☆18Updated 4 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆81Updated 3 years ago
• balajiln / pgbart
  Particle Gibbs for Bayesian Additive Regression Trees
  ☆32Updated 9 years ago
• TaddyLab / bayesian-forest
  ☆31Updated 8 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆90Updated 3 years ago
• janvdvegt / KernelMixtureNetwork
  Kernel Mixture Network implementation with some minor tweaks
  ☆45Updated 7 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆42Updated 6 years ago
• fonnesbeck / PyMC3_DataScienceLA
  PyMC3 tutorial for DataScience LA (January 2017)
  ☆68Updated 6 years ago
• shunsukeaihara / pydtw
  Fast Imprementation of Dynamic Time Warping For Python
  ☆42Updated last year
• franrruiz / p-emb
  Exponential family embeddings (Poisson or Bernoulli) for discrete data
  ☆32Updated 5 years ago
• AmazaspShumik / Mixture-Models
  Hierarchical Mixture of Experts,Mixture Density Neural Network
  ☆45Updated 7 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆59Updated 7 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆62Updated 5 years ago
• aflaxman / pymc-examples
  PyMC Example Notebooks
  ☆75Updated 10 years ago
• JackKelly / bayesianchangepoint
  An implementation of Adams & MacKay 2007 "Bayesian Online Changepoint Detection"
  ☆31Updated 10 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 6 years ago
• tmadl / sklearn-interpretable-tree
  Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)
  ☆46Updated 3 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆58Updated 7 years ago
• pierreablin / autoptim
  Automatic differentiation + optimization
  ☆104Updated 5 years ago
• chrisorm / pydata-2018
  ☆63Updated 6 years ago
• maxwshen / iap-cidl
  Causal Inference & Deep Learning, MIT IAP 2018
  ☆85Updated 6 years ago
• itsrainingdata / sparsebn
  Software for learning sparse Bayesian networks
  ☆43Updated 4 years ago
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated last year
• LucaAmbrogioni / Brancher
  A python library for stochastic variational inference and differentiable probabilistic programming
  ☆32Updated 5 years ago
• kafluette / fastfood
  ☆15Updated this week
• ceshine / recurrent-dropout-experiments
  ☆16Updated 5 years ago
• powerscorinne / GLRM
  ☆97Updated 6 years ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 12 years ago
• jonsedar / pymc3_vs_pystan
  Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/pre…
  ☆128Updated 8 years ago