386 Open source projects that are alternatives of or similar to Beta Vae

Experiments for understanding disentanglement in VAE latent representations

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

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

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

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

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

Ladder Variational Autoencoders (LVAE) in PyTorch

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

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

The Partitioning Around Medoids (PAM) implementation of the K-Medoids algorithm in Python [Unmaintained]

[TIP2020] Pytorch implementation of "Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network"

Deep-learning approaches to object recognition from 3D data

Parametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020

DCGAN Implementation using PyTorch in both C++ and Python

(ICCV 2021) Code for "Unsupervised Layered Image Decomposition into Object Prototypes" paper

AAAI 2018 - Unsupervised video summarization with deep reinforcement learning (PyTorch)

Unsupervised Controllable Text Generation (Applied to text Formalization)

Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)

High performance unsupervised text tokenization for Ruby

Find nodes in hierarchical clustering that are statistically significant

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

[CVPR2020] Adversarial Latent Autoencoders

(NeurIPS 2020 oral) Code for "Deep Transformation-Invariant Clustering" paper

Chainer implementation of deep-INFOMAX

Model for learning document embeddings along with their uncertainties

ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation

Here is the official implementation of the model KD3A in paper "KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation".

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)

Pytorch implementation of Hyperspherical Variational Auto-Encoders

🧶 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

和（he for objective-c） —— “信息熵减机系统”

Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization (TPAMI2018)

Self-Supervised depth kalilia

Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).

Implementing machine learning algorithms from scratch.

Repository for Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction (CVPR2019)

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

A developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

Study Friendly Implementation of DCGAN in Tensorflow

Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"

SelFlow: Self-Supervised Learning of Optical Flow

Recurrent Variational Autoencoder with Dilated Convolutions that generates sequential data implemented in pytorch

music generation with a classifying variational autoencoder (VAE) and LSTM

Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control.

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

Assessing Source Code Semantic Similarity with Unsupervised Learning

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

[ECCV'20] Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation

Mining Discourse Markers for Unsupervised Sentence Representation Learning

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

Unsupervised Speech Decomposition Via Triple Information Bottleneck

Machine Learning (EE 5184) in NTU

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

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

Implementation of Sequential Attend, Infer, Repeat (SQAIR)

PyTorch implementation of the NIPS 2017 paper - Unsupervised Learning of Disentangled Representations from Video

CorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.

TCyb 2018: Graph learning for multiview clustering