889 Open source projects that are alternatives of or similar to srVAE

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

Experiments for understanding disentanglement in VAE latent representations

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

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

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

Ladder Variational Autoencoders (LVAE) in PyTorch

Protein function prediction using a variational autoencoder

Invariant representation learning from imaging and spectral data

Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets

Implementation of VLAE

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

Collection of generative models in Tensorflow

Variational Autoencoder trained by Feature Perceputal Loss

A Tensorfflow implementation of Attend, Infer, Repeat

Spectral Normalization for Keras Dense and Convolution Layers

A stable algorithm for GAN training

Unsupervised learning and generative models in python/pytorch.

No description or website provided.

🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib

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

Vector Quantized Autoregressive Predictive Coding (VQ-APC)

Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)

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

Generative Adversarial Networks in TensorFlow 2.0

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

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Torch Implemention of ECCV'16 paper: Attribute2Image

A combination of VAE's and Diffusion Models for efficient, controllable and high-fidelity generation from low-dimensional latents

Awesome Graph Self-Supervised Learning

Deep Recurrent Generative Decoder for Abstractive Text Summarization in DyNet

Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling

PyTorch implementation of VQ-VAE-2 from "Generating Diverse High-Fidelity Images with VQ-VAE-2"

Official adversarial mixup resynthesis repository

Neural Relation Understanding: neural cardinality estimators for tabular data

A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).

Code accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"

pyMCR: Multivariate Curve Resolution for Python

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

This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Assessing Generative Models via Precision and Recall (official repository)

PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

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

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

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

Official repository for the ShapeFormer Project

PC-DARTS (PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search, published in ICLR 2020) implemented in Tensorflow 2.0+. This is an unofficial implementation.

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.

A numpy based CNN implementation for classifying images

Proto-RL: Reinforcement Learning with Prototypical Representations

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

Inspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.

Generative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)

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

Variational autoencoder for anomaly detection (in PyTorch).

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

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

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

A VAE written entirely in Numpy/Cupy