Alternatives and similar repositories for MLExp

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

• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• izmailovpavel / TTGP
  ☆26Updated 7 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆37Updated 5 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
• jjfeng / spinn
  Sparse-input neural networks
  ☆23Updated 2 years ago
• JeanKossaifi / ifi-summer-school
  Slides and notebooks for the IfI Summer School 2018 on Machine Learning
  ☆36Updated 7 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• datasailors / bayesian_calibration
  Bayesian calibration using Tensorflow Probability
  ☆35Updated 6 years ago
• erichson / ristretto
  Randomized Dimension Reduction Library
  ☆115Updated 4 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• zjost / bayesian-linear-regression
  A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/
  ☆82Updated 8 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆63Updated 8 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• gpschool / gpss18
  Gaussian Process and Uncertainty Quantification Summer School 2018
  ☆31Updated 2 years ago
• yuqirose / tensor_train_RNN
  Clean repo for tensor-train RNN implemented in TensorFlow
  ☆68Updated 5 years ago
• bnaul / IrregularTimeSeriesAutoencoderPaper
  ☆65Updated 11 months ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• fonnesbeck / gp_tutorial_pydata
  PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3
  ☆15Updated 7 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆183Updated 6 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 7 years ago
• vsmolyakov / ml
  machine learning
  ☆39Updated 6 years ago
• ksanjeevan / randomforest-density-python
  Random Forests for Density Estimation in Python
  ☆27Updated last year
• pablormier / machine-learning-notebooks
  Notes on Pattern Recognition and Machine Learning
  ☆10Updated 8 years ago