Alternatives and similar repositories for MLExp

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

• izmailovpavel / TTGP
  ☆26Updated 7 years ago
• yuqirose / tensor_train_RNN
  Clean repo for tensor-train RNN implemented in TensorFlow
  ☆69Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• misokg / NIPS2017
  Multi-Information Source Optimization
  ☆24Updated 6 years ago
• bnaul / IrregularTimeSeriesAutoencoderPaper
  ☆65Updated last year
• jjfeng / spinn
  Sparse-input neural networks
  ☆23Updated 2 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 7 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆38Updated 6 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆27Updated 6 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 8 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
• shz9 / csc2541-ml-project
  Modeling Uncertainty in RNNs for Time Series Forecasting
  ☆15Updated 8 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated 2 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 6 years ago
• gpschool / gpss18
  Gaussian Process and Uncertainty Quantification Summer School 2018
  ☆31Updated 3 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 5 years ago
• datasailors / bayesian_calibration
  Bayesian calibration using Tensorflow Probability
  ☆35Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆87Updated 4 years ago
• anassinator / bnn
  Bayesian Neural Network in PyTorch
  ☆93Updated last year
• NervanaSystems / aidc-2018-timeseries
  Deep learning for time-series data
  ☆50Updated 3 years ago
• bperezorozco / ordinal_tsf
  ☆29Updated 6 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆184Updated 7 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆64Updated 8 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆25Updated last year
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆45Updated 3 weeks ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago