Alternatives and similar repositories for misgan

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

• probabilistic-learning / HI-VAE
  ☆91Updated 2 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆41Updated last year
• lstruski / Processing-of-missing-data-by-neural-networks
  ☆43Updated 6 years ago
• rcamino / imputation-dgm
  Code for the paper "Improving Missing Data Imputation with Deep Generative Models"
  ☆32Updated 6 years ago
• Harry24k / MIDA-pytorch
  PyTorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"
  ☆28Updated 6 years ago
• mtsang / neural-interaction-detection
  Detecting Statistical Interactions from Neural Network Weights
  ☆49Updated 5 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• chaoshangcs / VIGAN
  PyTorch implementation of VIGAN
  ☆40Updated 8 years ago
• ananyahjha93 / multi-level-vae
  This repository contains a pytorch implementation for the paper: Multi-Level Variational Autoencoder (https://arxiv.org/abs/1705.08841), …
  ☆71Updated 3 years ago
• slim1017 / VaDE
  Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering
  ☆307Updated 7 years ago
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• zhiyongc / GRU-D
  Gated Recurrent Unit with a Decay mechanism for Multivariate Time Series with Missing Values
  ☆119Updated 6 years ago
• mmcdermott / CWR-GAN
  The code for the cycle wasserstein regression generative adversarial network model for semi supervised bi-directional regression.
  ☆23Updated 7 years ago
• mkocaoglu / CausalGAN
  ☆145Updated 8 years ago
• jsyoon0823 / GAIN
  Codebase for Generative Adversarial Imputation Networks (GAIN) - ICML 2018
  ☆404Updated 3 years ago
• tijiang13 / Semi-supervised-VAE
  ☆24Updated 6 years ago
• ermongroup / ssdkl
  Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
  ☆76Updated 6 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆132Updated 5 years ago
• ioanabica / Counterfactual-Recurrent-Network
  Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…
  ☆62Updated last year
• ratschlab / SOM-VAE
  TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199
  ☆197Updated 2 years ago
• rymc / n2d
  A deep clustering algorithm. Code to reproduce results for our paper N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of …
  ☆138Updated last year
• alexlyzhov / latent-subspaces
  Implementation of "Learning latent subspaces in variational autoencoders"
  ☆20Updated 5 years ago
• zhampel / clusterGAN
  Pytorch Implementation of ClusterGAN (arXiv:1809.03627)
  ☆96Updated 2 years ago
• sedelmeyer / wasserstein-auto-encoder
  A brief tutorial on the Wasserstein auto-encoder
  ☆84Updated 6 years ago
• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆87Updated 6 years ago
• vlukiyanov / pt-sdae
  PyTorch implementation of SDAE (Stacked Denoising AutoEncoder)
  ☆127Updated 5 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆64Updated 5 years ago
• OctoberChang / klcpd_code
  Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)
  ☆60Updated 2 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
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆102Updated 7 years ago