Alternatives and similar repositories for Mutual-Information

Users that are interested in Mutual-Information are comparing it to the libraries listed below

• JamesRitchie / scikit-rvm
  Relevance Vector Machine implementation using the scikit-learn API.
  ☆237Updated 4 months ago
• Craigacp / MIToolbox
  Mutual Information functions for C and MATLAB
  ☆144Updated 7 years ago
• jiayuzhou / MALSAR
  Multi-task learning via Structural Regularization
  ☆135Updated 4 years ago
• anhncs / Probabilistic-Graphical-Models
  Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.
  ☆104Updated 12 years ago
• rupy / GCCA
  Generalized Canonical Correlation Analysis
  ☆51Updated 8 years ago
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆61Updated 5 years ago
• wxiao0421 / onlineRPCA
  Online Robust Principal Component Analysis
  ☆101Updated 5 years ago
• peiyunh / mat-vae
  A MATLAB implementation of Auto-Encoding Variational Bayes
  ☆48Updated 9 years ago
• epfl-lts2 / pyunlocbox
  A Python convex optimization package using proximal splitting methods
  ☆119Updated 3 months ago
• akusok / hpelm
  High performance implementation of Extreme Learning Machines (fast randomized neural networks).
  ☆201Updated 10 months ago
• rmgarnett / active_learning
  Active learning toolbox for MATLAB
  ☆46Updated 8 years ago
• Craigacp / FEAST
  A FEAture Selection Toolbox for C/C+, Java, and Matlab/Octave.
  ☆72Updated 3 years ago
• lucastheis / deepbelief
  Code for training and evaluating restricted Boltzmann machines (RBMs) and deep belief networks (DBNs).
  ☆61Updated 14 years ago
• Jianbo-Lab / CCM
  ☆74Updated 7 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆64Updated 8 years ago
• kimjingu / nonnegfac-python
  Python toolbox for nonnegative matrix factorization
  ☆115Updated 7 years ago
• gallantlab / pyrcca
  Regularized kernel canonical correlation analysis in Python
  ☆257Updated 4 years ago
• clinicalml / dmm
  Deep Markov Models
  ☆132Updated 6 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆67Updated 8 years ago
• jjfeng / spinn
  Sparse-input neural networks
  ☆23Updated 2 years ago
• ramarlina / DenoisingAutoEncoder
  Python implementation of Stacked Denoising Autoencoders for unsupervised learning of high level feature representation
  ☆150Updated 10 years ago
• trigeorgis / Deep-Semi-NMF
  Theano-based implementation of Deep Semi-NMF.
  ☆121Updated 10 years ago
• drumichiro / nmf-and-ntf
  The sample code to study non-negative matrix and tensor factorization.
  ☆38Updated 5 years ago
• steverab / tensor-gmm
  Implementation of learning a Gaussian mixture model using tensor decomposition.
  ☆15Updated 8 years ago
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆141Updated 7 years ago
• ncullen93 / pyBN
  Bayesian Networks in Python
  ☆149Updated 2 years ago
• IvanoLauriola / MKLpy
  A package for Multiple Kernel Learning in Python
  ☆131Updated 2 years ago
• mstrazar / mklaren
  A Python Multiple kernel learning library.
  ☆57Updated 6 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆44Updated 11 years ago
• djsutherland / opt-mmd
  Learning kernels to maximize the power of MMD tests
  ☆211Updated 7 years ago