Alternatives and similar repositories for vde

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

• ratschlab / SOM-VAE
  TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199
  ☆197Updated 2 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆246Updated 3 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated last year
• wiskott-lab / sklearn-sfa
  This project provides Slow Feature Analysis as a scikit-learn-style package.
  ☆41Updated last year
• simonkamronn / kvae
  Kalman Variational Auto-Encoder
  ☆136Updated 6 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆234Updated 4 years ago
• kormilitzin / the-signature-method-in-machine-learning
  Foundations and Applications
  ☆99Updated 5 years ago
• TeaPearce / Deep_Learning_Prediction_Intervals
  ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'
  ☆91Updated 5 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆63Updated 8 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• 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
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• ratschlab / dpsom
  Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'
  ☆70Updated 4 years ago
• yabozkurt / gmvae
  Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'
  ☆20Updated 5 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆196Updated 2 years ago
• blt2114 / CDE_with_BNF
  Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows
  ☆22Updated 6 years ago
• shibuiwilliam / keras_gpyopt
  Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.
  ☆57Updated 7 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• gmum / pykernels
  Python library for working with kernel methods in machine learning
  ☆121Updated 6 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• Jianbo-Lab / CCM
  ☆74Updated 6 years ago
• axelbrando / Mixture-Density-Networks-for-distribution-and-uncertainty-estimation
  A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
  ☆352Updated 8 years ago
• JamesRitchie / scikit-rvm
  Relevance Vector Machine implementation using the scikit-learn API.
  ☆238Updated last week
• dfm / gp
  A tutorial about Gaussian process regression
  ☆188Updated 4 years ago
• jamesrobertlloyd / gp-structure-search
  ☆238Updated 8 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆184Updated 6 years ago
• yuqirose / tensor_train_RNN
  Clean repo for tensor-train RNN implemented in TensorFlow
  ☆69Updated 6 years ago
• choderalab / cpdetect
  Change Point detection
  ☆26Updated 6 years ago