Alternatives and similar repositories for orca

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

• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆63Updated 8 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆216Updated 6 years ago
• jingxil / Neural-Decision-Forests
  An implementation of the Deep Neural Decision Forests in PyTorch
  ☆165Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated last year
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated last year
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆59Updated 4 years ago
• bnpy / bnpy
  Bayesian nonparametric machine learning for Python
  ☆228Updated 2 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• ebonilla / mtgp
  Multi-task Gaussian Process
  ☆43Updated 10 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆235Updated 4 years ago
• ncullen93 / pyBN
  Bayesian Networks in Python
  ☆149Updated 2 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆40Updated 6 years ago
• dganguli / robust-pca
  A simple Python implementation of R-PCA
  ☆245Updated 2 years ago
• jlsuarezdiaz / pyDML
  Distance Metric Learning Algorithms for Python
  ☆173Updated 4 years ago
• erichson / ristretto
  Randomized Dimension Reduction Library
  ☆115Updated 4 years ago
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆185Updated 11 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆80Updated 6 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆64Updated 6 years ago
• clinicalml / dmm
  Deep Markov Models
  ☆133Updated 6 years ago
• mstrazar / mklaren
  A Python Multiple kernel learning library.
  ☆57Updated 6 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆38Updated 2 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• Jianbo-Lab / CCM
  ☆74Updated 6 years ago
• jiayuzhou / MALSAR
  Multi-task learning via Structural Regularization
  ☆134Updated 4 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago