Wasserstein Auto-Encoders
☆507Jun 28, 2018Updated 7 years ago
Alternatives and similar repositories for wae
Users that are interested in wae are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of Wasserstein Auto-Encoders☆298Aug 7, 2020Updated 5 years ago
- ☆66Apr 15, 2019Updated 6 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Mar 19, 2018Updated 7 years ago
- A brief tutorial on the Wasserstein auto-encoder☆86Dec 13, 2018Updated 7 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆92Jun 6, 2018Updated 7 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆101Sep 24, 2018Updated 7 years ago
- Pytorch implementation of Wasserstein Auto-Encoders☆25Feb 7, 2018Updated 8 years ago
- Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling☆233May 6, 2018Updated 7 years ago
- Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"☆529Nov 22, 2018Updated 7 years ago
- Implementation of VLAE☆214Dec 21, 2017Updated 8 years ago
- Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation☆470Apr 2, 2019Updated 6 years ago
- Reimplementation of Wasserstein Auto Encoder (WAE) with Wasserstein GAN based penalty D_Z in Tensorflow☆12Mar 28, 2019Updated 6 years ago
- Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"☆244Aug 6, 2018Updated 7 years ago
- Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.☆7,496Mar 24, 2024Updated last year
- Code for reproducing experiments in "Improved Training of Wasserstein GANs"☆2,401Jun 6, 2018Updated 7 years ago
- disentanglement_lib is an open-source library for research on learning disentangled representations.☆1,420May 16, 2021Updated 4 years ago
- PyTorch implementations of algorithms for density estimation☆586May 13, 2021Updated 4 years ago
- Chainer implementation of adversarial autoencoder (AAE)☆256Mar 7, 2018Updated 7 years ago
- Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders☆215Mar 4, 2020Updated 6 years ago
- Deep generative model for sentiment analysis☆34Mar 13, 2017Updated 8 years ago
- A implementation of FactorVAE from the paper Disentangling by Factorising, Kim & Mnih 2018 (https://arxiv.org/pdf/1802.05983.pdf )☆16Apr 24, 2018Updated 7 years ago
- Code for reproducing results of NIPS 2014 paper "Semi-Supervised Learning with Deep Generative Models"☆516Jan 25, 2015Updated 11 years ago
- Dataset to assess the disentanglement properties of unsupervised learning methods☆528Jan 3, 2021Updated 5 years ago
- Optimizing control variates for black-box gradient estimation☆163Jul 26, 2019Updated 6 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Apr 1, 2020Updated 5 years ago
- GANs with spectral normalization and projection discriminator☆1,102Nov 12, 2019Updated 6 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆208Apr 13, 2018Updated 7 years ago
- source code of the paper Graphical Generative Adversarial Networks☆71Jun 10, 2019Updated 6 years ago
- Code for the paper "Adversarial Generator-Encoder Networks"☆287Jun 28, 2018Updated 7 years ago
- ☆3,245Dec 26, 2018Updated 7 years ago
- Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"☆3,180Jul 23, 2024Updated last year
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆34May 11, 2023Updated 2 years ago
- Code for the paper "Adversarially Regularized Autoencoders (ICML 2018)" by Zhao, Kim, Zhang, Rush and LeCun☆399Apr 11, 2020Updated 5 years ago
- The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)☆1,092Dec 6, 2022Updated 3 years ago
- Tensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)☆123Dec 10, 2017Updated 8 years ago
- Implementations of various VAE-based semi-supervised and generative models in PyTorch☆709Mar 2, 2020Updated 6 years ago
- Deep generative models for semi-supervised learning.☆109Nov 21, 2016Updated 9 years ago
- POT : Python Optimal Transport☆2,763Feb 24, 2026Updated last week
- Denoising Adversairal Autoencoders☆41Jun 13, 2017Updated 8 years ago