Alternatives and similar repositories for bayesian-linear-regression

Users that are interested in bayesian-linear-regression are comparing it to the libraries listed below

• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• mbinkowski / nntimeseries
  ☆209Updated 7 years ago
• alexsosn / MarslandMLAlgo
  Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.
  ☆148Updated 4 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 5 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆63Updated 8 years ago
• clinicalml / dmm
  Deep Markov Models
  ☆133Updated 6 years ago
• ChadFulton / pymar
  Markov Switching Models for Statsmodels
  ☆23Updated 9 years ago
• karlnapf / ds3_kernel_testing
  Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"
  ☆26Updated 6 years ago
• Rachnog / Neural-Networks-for-Differential-Equations
  UNIVR PDE course project and just for fun
  ☆117Updated 8 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• lopatovsky / HMMs
  Continuous-time Hidden Markov Model
  ☆102Updated last year
• philipperemy / tensorflow-cnn-time-series
  Feeding images of time series to Conv Nets! (Tensorflow + Keras)
  ☆49Updated 8 years ago
• sachinruk / KerasQuantileModel
  Quantile Regression using Deep Learning. An alternative to Bayesian models to get uncertainty.
  ☆76Updated 7 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆61Updated 8 years ago
• fonnesbeck / gp_tutorial_pydata
  PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3
  ☆15Updated 7 years ago
• ChadFulton / fulton_statsmodels_2017
  State Space Estimation of Time Series Models in Python: Statsmodels
  ☆44Updated 8 years ago
• shark8me / Building_Probabilistic_Graphical_Models_in_Python
  Source code for the book "Building Probabilistic Graphical Models in Python"
  ☆30Updated 8 years ago
• rsnirwan / GPLVMsInFinance
  Applications of Gaussian Process Latent Variable Models in Finance
  ☆11Updated 3 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆92Updated 4 years ago
• jmetzen / kernel_regression
  Implementation of Nadaraya-Watson kernel regression with automatic bandwidth selection compatible with sklearn.
  ☆81Updated 9 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• abrvkh / WaveNet_simple
  A simple implementation of the WaveNet model for time series forecasting
  ☆26Updated 7 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆67Updated 6 years ago
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• sjblim / rnf-ijcnn-2020
  Recurrent Neural Filters for Time Series Prediction
  ☆24Updated 5 years ago
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated 2 years ago
• Hvass-Labs / MetaOps
  Tuning the Parameters of Heuristic Optimizers (Meta-Optimization / Hyper-Parameter Optimization)
  ☆55Updated 6 years ago
• manuwhs / BayesianRNN
  Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.
  ☆40Updated 7 years ago
• dobriban / Topics-in-deep-learning
  Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
  ☆95Updated 2 years ago