795 Open source projects that are alternatives of or similar to Disentangling Vae

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.

Pytorch implementation of β-VAE

Tensorflow implementation of conditional variational auto-encoder for MNIST

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Tensorflow implementation of variational auto-encoder for MNIST

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

Ladder Variational Autoencoders (LVAE) in PyTorch

Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Collection of generative models in Tensorflow

📜 Self-Supervised Learning from Images: Up-to-date reading list.

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds (CVPR 2020)

Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

Implementation of VLAE

Keras implementation of Representation Learning with Contrastive Predictive Coding

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"

PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

Vector Quantized Autoregressive Predictive Coding (VQ-APC)

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

Python implementation of bag-of-concepts

Training and evaluating a variational autoencoder for pan-cancer gene expression data

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.

An implementation of "Community Preserving Network Embedding" (AAAI 2017)

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

SCAN: Learning to Classify Images without Labels (ECCV 2020), incl. SimCLR.

Playing with MNIST. Machine Learning. Generative Models.

No description or website provided.

Contrastive Predictive Coding for Automatic Speaker Verification

Awesome Graph Self-Supervised Learning

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

Assessing Generative Models via Precision and Recall (official repository)

Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

Tensorflow implementation of adversarial auto-encoder for MNIST

Unsupervised Feature Learning via Non-parametric Instance Discrimination

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

Implementation of VAE and Style-GAN Architecture Achieving State of the Art Reconstruction

Official adversarial mixup resynthesis repository

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

Invariant representation learning from imaging and spectral data

PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

Unsupervised Representation Learning for Singing Voice Separation

Simplified version of "State Representation Learning for Control: An Overview" bibliography

Learning about Haskell with Variational Autoencoders

A comprehensive list of awesome contrastive self-supervised learning papers.

Pytorch implementation of "A Simple Framework for Contrastive Learning of Visual Representations"

Pytorch implementation of Hyperspherical Variational Auto-Encoders

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Proto-RL: Reinforcement Learning with Prototypical Representations