A Collection of Variational Autoencoders (VAE) in PyTorch.

deep-learning reproducible-research architecture pytorch vae beta-vae paper-implementations gumbel-softmax celeba-dataset wae variational-autoencoders pytorch-implementation dfc-vae iwae vqvae vae-implementation pytorch-vae

• Updated Mar 21, 2025
• Python

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

benchmarking reproducible-research pytorch comparison vae pixel-cnn reproducibility beta-vae vae-gan normalizing-flows variational-autoencoder vq-vae wasserstein-autoencoder vae-implementation vae-pytorch

• Updated Jul 31, 2024
• Python

Implementation of mutual learning model between VAE and GMM.

machine-learning pytorch gaussian-mixture-models vae gmm cognitive-architecture variational-autoencoder pytorch-implementation vae-implementation vae-pytorch vae-gmm generative-ai

• Updated Oct 8, 2025
• Python

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.

c deep-neural-networks simulator deep-learning cpp statistical-analysis vae deeplearning autoencoders test-statistic variational-autoencoder variational-autoencoders deeplearning-ai vae-implementation continuous-bernoulli point-estimator

• Updated May 6, 2024
• C++

Dirichlet-Variational Auto-Encoder by PyTorch

machine-learning deep-neural-networks deep-learning pytorch vae variational-autoencoder dirichlet pytorch-implementation vae-implementation vae-pytorch paper-with-code dirichlet-vae generative-ai

• Updated Oct 8, 2025
• Jupyter Notebook

Pytorch implementation of Gaussian Mixture Variational Autoencoder GMVAE

pytorch mnist gaussian-mixture-models variational-autoencoder gmvae latent-space vae-implementation vae-pytorch

• Updated Jun 23, 2024
• Python

Implementation of LiteVAE

pytorch vae variational-autoencoder vae-implementation vae-pytorch

• Updated Feb 11, 2025
• Python

Tensorflow 2.x implementation of the beta-TCVAE (arXiv:1802.04942).

deep-learning unsupervised-learning tensorflow2 vae-implementation

• Updated Nov 12, 2019
• Python

An official repository for a VAE tutorial of Probabilistic Modelling and Reasoning - a University of Edinburgh master's course.

vae variational-inference probabilistic-models variational-autoencoder probabilistic-inference vae-implementation gradient-estimation

• Updated Jan 2, 2024
• Jupyter Notebook

Learn Machine learning by doing exercises and intuitive animations

transformers matrix-multiplication neural-networks gradient-descent learning-by-doing attention-mechanism lstm-neural-networks ai-agents hands-on-machine-learning vae-implementation stable-diffusion llms

• Updated Sep 18, 2026
• JavaScript

Symbol emergence using Variational Auto-Encoder and Gaussian Mixture Model (Inter-GMM-VAE)~VAEを活用した実画像からの記号創発~

machine-learning pytorch gaussian-mixture-models vae multiagent-systems gmm variational-autoencoder naming-game pytorch-implementation vae-implementation vae-pytorch generative-ai

• Updated Oct 8, 2025
• Python

Topics include function approximation, learning dynamics, using learned dynamics in control and planning, handling uncertainty in learned models, learning from demonstration, and model-based and model-free reinforcement learning.

pytorch trajectory-optimization gaussian-processes robot-learning model-predictive-controller robot-manipulation gpytorch vae-implementation mppi

• Updated Feb 7, 2024
• Jupyter Notebook

Python implementation of N-gram Models, Log linear and Neural Linear Models, Back-propagation and Self-Attention, HMM, PCFG, CRF, EM, VAE

natural-language-processing n-grams log-linear-model em-algorithm hmm-viterbi-algorithm crf-model self-attentive-rnn self-attention pcfg vae-implementation

• Updated Aug 20, 2020
• Python

Pytorch版本实现的VAE和公式推导

vae vae-implementation vae-pytorch

• Updated Nov 10, 2025
• Python

Variational Auto Encoders (VAEs), Generative Adversarial Networks (GANs) and Generative Normalizing Flows (NFs) and are the most famous and powerful deep generative models.

deep-neural-networks deep-learning vae cvae vae-implementation

• Updated Jan 14, 2020
• Python

Optimized PyTorch/Triton MiniMax H3 video VAE for ComfyUI, with reproducible benchmarks and optional mixed INT8 acceleration—no TensorRT engine required.

cuda pytorch triton vae minimax int8 video-generation vae-implementation vae-pytorch int8-quantization comfyui torch-compile comfyui-custom-node gpt-optimization minimax-h3

• Updated Oct 8, 2026
• Python

A re-implementation of the Sentence VAE paper, Generating Sentences from a Continuous Space

text-generation gru rnn vae vae-implementation vae-pytorch text-generation-using-rnn

• Updated Sep 22, 2022
• Python

Implementation of the variational autoencoder with PyTorch and Fastai

pytorch vae fastai variational-autoencoder variational-autoencoders vae-implementation

• Updated Jun 27, 2020
• Jupyter Notebook

Utilized a VAE (Variational Autoencoder) and CGAN (Conditional Generative Adversarial Network) models to generate synthetic chatter signals, addressing the challenge of imbalanced data in turning operations. Compared othe performance of synthetic chatter signals.

tensorflow matlab pytorch vae-implementation cgan-training

• Updated Jan 31, 2024
• Jupyter Notebook

gan vae domain-adaptation wasserstein-gan cyclegan bitmoji celeba-dataset energy-based-model vae-implementation vae-pytorch constrastive-learning dsprites-data vae-cnn adversarial-discriminative-domain-adaptation

• Updated Dec 9, 2022
• Jupyter Notebook