209 Open source projects that are alternatives of or similar to AutoEncoders

Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf)

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Shared Latent Space VAE's

Next RecSys Library

Experiments with Adversarial Autoencoders using Keras

Tensorflow implementation of variational auto-encoder for MNIST

Tensorflow implementation of conditional variational auto-encoder for MNIST

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rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

Training and evaluating a variational autoencoder for pan-cancer gene expression data

Focal Frequency Loss for Generative Models

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"

This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

Autoencoder trained on ImageNet Using Torch 7

Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)

We got a stew going!

Global NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"

A new approach to video compression by refining the shortcomings of conventional approach and substituting each traditional component with their neural network counterpart. Our proposed work consists of motion estimation, compression and compensation and residue compression, learned end-to-end to minimize the rate-distortion trade off. The whole…

Deep learning image autoencoder that not depends on image resolution

Colorizing B&W Photos with Neural Networks

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'

Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Variational autoencoder for anomaly detection (in PyTorch).

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Convolutional AutoEncoder application on MRI images

SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

Implementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder

Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Variational autoencoder for Lego minifig faces

Dual CNN Models for Unsupervised Monocular Depth Estimation

This is my attempt to reproduce and extend the results in the paper "An Introduction to Deep Learning for the Physical Layer" by Tim O'Shea and Jakob Hoydis

Lagrangian VAE

Interactive Visual Machine Learning Demos.

Open-source code for our paper: Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

Unsupervised (Self-Supervised) Clustering of Seismic Signals Using Deep Convolutional Autoencoders

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

Real time face landmarking using decision trees and NN autoencoders

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch

Invariant representation learning from imaging and spectral data

Hands-on in-person workshop for Deep Learning with TensorFlow

📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈

An implementation of VAEGAN (variational autoencoder + generative adversarial network).

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.

Image retrieval program made in Tensorflow supporting VGG16, VGG19, InceptionV3 and InceptionV4 pretrained networks and own trained Convolutional autoencoder.

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Noise removal from images using Convolutional autoencoder

Tensorflow implementation of adversarial auto-encoder for MNIST

Torch Implemention of ECCV'16 paper: Attribute2Image

eForest: Reversible mapping between high-dimensional data and path rule identifiers using trees embedding