[ICLR 2025 & COLM 2025] Official PyTorch implementation of the Forgetting Transformer and Adaptive Computation Pruning

A minimal PyTorch implementation of the VQ-VAE model described in "Neural Discrete Representation Learning".

Sentence VAE using the Transformer encoder-decoder architecture.

Transformer Variational Autoencoder experiment

PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349

Deep learning for single-cell transcript counts

Implementation of the Auto-Encoding Variational Bayes paper in Pytorch with detailed explanation.

Making Protein folding accessible to all!

"Deep Generative Modeling": Introductory Examples

A library for making Transformer Variational Autoencoders. (Extends the Huggingface/transformers library.)

Variational Transformer Autoencoder with Manifolds Learning

A Collection of Variational Autoencoders (VAE) in PyTorch.

Variational AutoEncoder + ResNet Transfer Learning

Beta-VAE, Conditional-VAE, Total Correlation-VAE, FactorVAE, Relevance Factor-VAE, Multi-Level VAE, (Soft)-IntroVAE (Beta-Version), LVAE, VLAE, VaDE and MFCVAE implemented in Tensorflow 2

the reproduce of Variational Deep Embedding : A Generative Approach to Clustering Requirements by pytorch

PyTorch Implementation of Kingma's M2 VAE

a variational autoencoder method for clustering single-cell mutation data

Deep Generative Models for Learning Gene Expression Profile Latent Representations from LINCS L1000 data

A repository that will hold my experiments with various variational models

Minimalist implementation of VQ-VAE in Pytorch

Vector (and Scalar) Quantization, in Pytorch

Sample tutorials for training Natural Language Processing Models with Transformers

Pre-training BERT masked language models with custom vocabulary

R Package 📦 Containing the Datasaurus Dozen datasets 📊