A wizard's guide to Adversarial Autoencoders

Tensorflow implementation of Adversarial Autoencoders

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Tensorflow implementation of adversarial auto-encoder for MNIST

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…

Open-set Recognition with Adversarial Autoencoders

Tensorflow 2.0 implementation of Adversarial Autoencoders

Adversarial Auto-encoders for Speech Based Emotion Recogntion

Repository for the AugmentedPCA Python package.

The source of the solution of SHL recognition challenge 2019 based on Semi-supervised Adversarial Autoencoders (AAE) for Human Activity Recognition (HAR)

A PyTorch implementation of Adversarial Autoencoders for unsupervised classification

Adversarial_Autoencoder by using tensorflow

Data and Trained models can be downloaded from https://goo.gl/7PrKD2

A repository containing my submissions for the evaluation test for prospective GSoC applicants for the DeepLense project

Pytorch implementation of Adversarial Autoencoder

Adversarial Autoencoder based text summarizer and comparison of frequency based, graph based, and several different iterations of clustering based text summarization techniques

Investigation into Generative Neural Networks.

Companion repository for the blog article on neural text summarization with a denoising-autoencoder