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Top 129 autoencoder open source projects

Keras Idiomatic Programmer
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Ad examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Dancenet
DanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)
Generative Models
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Tensorflow Mnist Vae
Tensorflow implementation of variational auto-encoder for MNIST
Autoencoders
Torch implementations of various types of autoencoders
Deepsvg
[NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data.
Zhihu
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.
Hands On Deep Learning Algorithms With Python
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Noise2Noise-audio denoising without clean training data
Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoisi…
T3
[EMNLP 2020] "T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack" by Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, Bo Li
SAE-NAD
The implementation of "Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence"
video autoencoder
Video lstm auto encoder built with pytorch. https://arxiv.org/pdf/1502.04681.pdf
sldm4-h2o
Statistical Learning & Data Mining IV - H2O Presenation & Tutorial
AutoEncoders
Variational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras
abae-pytorch
PyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'
TensorFlow-Autoencoders
Implementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder
time-series-autoencoder
📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈
Encoder-Forest
eForest: Reversible mapping between high-dimensional data and path rule identifiers using trees embedding
Speech driven gesture generation with autoencoder
This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".
deep-steg
Global NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"
autoencoder for physical layer
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
maui
Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit
mae-scalable-vision-learners
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners
seq3
Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"
imagenet-autoencoder
Autoencoder trained on ImageNet Using Torch 7
Reducing-the-Dimensionality-of-Data-with-Neural-Networks
Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)
SESF-Fuse
SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion
Video-Compression-Net
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…
peax
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Continuous-Image-Autoencoder
Deep learning image autoencoder that not depends on image resolution
topological-autoencoders
Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
GATE
The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"
probabilistic nlg
Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
Unsupervised Deep Learning
Unsupervised (Self-Supervised) Clustering of Seismic Signals Using Deep Convolutional Autoencoders
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