Popular GitHub Repositories for Autoencoder

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

Collection of generative models in Tensorflow

[CVPR2020] Adversarial Latent Autoencoders

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

[ECCV2024] Video Foundation Models & Data for Multimodal Understanding

Advanced Deep Learning with Keras, published by Packt

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

Use unsupervised and supervised learning to predict stocks

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

[ICLR'23 Spotlight?] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"

"Deep Generative Modeling": Introductory Examples

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

Tensorflow implementation of Variational Auto-Encoder