Alternatives and similar repositories for exp-machines:

Users that are interested in exp-machines are comparing it to the libraries listed below

• DeepLearningDTU / Summerschool_2015
  Deep Learning DTU summer school 2015
  ☆22Updated 8 years ago
• taku-y / pymc3
  Probabilistic Programming in Python. Uses Theano as a backend and includes the NUTS sampler.
  ☆12Updated 7 years ago
• caglar / adasecant_wshp_paper
  Code for the arxiv paper
  ☆9Updated 9 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 6 years ago
• bshahr / torch-dngo
  Torch implementation of the Deep Network for Global Optimization (DNGO)
  ☆51Updated 8 years ago
• vene / pyowl
  Ordered Weighted L1 regularization for classification and regression in Python
  ☆52Updated 6 years ago
• davmre / treegp
  Gaussian Process Regression for Python/Numpy
  ☆14Updated 8 years ago
• pranv / lrh
  Learning RNN Hierarchies
  ☆45Updated 8 years ago
• HIPS / maxwells-daemon
  Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
  ☆32Updated 8 years ago
• GRAAL-Research / PAC-Bayes_sample_compress_for_kernel_methods
  Learning algorithms introduced in "A PAC-Bayes Sample Compression Approach to Kernel Methods" (ICML 2011)
  ☆9Updated 10 years ago
• automl / labwatch
  An extension to Sacred for automated hyperparameter optimization.
  ☆59Updated 6 years ago
• lucastheis / cmt
  Fast CPU implementations of several conditional probabilistic models
  ☆36Updated last year
• ofirnachum / uncertainty_gbm
  Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data
  ☆27Updated 8 years ago
• diogo149 / treeano
  more composable than other neural network libraries
  ☆42Updated 8 years ago
• vfleaking / rnnprop
  RNNprop
  ☆36Updated 7 years ago
• davidBelanger / tf-hypergrad
  simple example of gradient-based hyperparameter optimization using tensorflow
  ☆19Updated 8 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 9 years ago
• lisa-lab / GSN
  Efficient implementation of Generative Stochastic Networks
  ☆12Updated 11 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• ferrine / gelato
  Bayesian dessert for Lasagne
  ☆84Updated 7 years ago
• felixlaumon / nolearn_utils
  Utilities for nolearn.lasagne
  ☆21Updated 7 years ago
• kuleshov / tensor-factorization
  Tensor Factorization via Matrix Factorization
  ☆34Updated 8 years ago
• paulbertens / rank-ordered-autoencoder
  Rank Ordered Autoencoder implementation as described in https://arxiv.org/abs/1605.01749
  ☆33Updated 8 years ago
• cjf00000 / ScaCTM
  Scalable inference for Correlated Topic Models
  ☆30Updated 9 years ago
• cjratcliff / variational-dropout
  TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)
  ☆16Updated 7 years ago
• FurongHuang / TensorDecomposition4TopicModeling
  ☆20Updated 7 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 7 years ago
• soumith / deep_gitstats
  Based on SciPy's normalized git stats, adapted for Deep Learning frameworks
  ☆16Updated 7 years ago
• frank-hutter / fanova
  Functional ANOVA
  ☆27Updated 10 years ago
• craffel / Lasagne-tutorial
  Adding an ipynb tutorial to Lasagne
  ☆53Updated 7 years ago