128 Open source projects that are alternatives of or similar to autoencoder_for_physical_layer

中文的 tensorflow tutorial with jupyter notebooks

Implementation of the stacked denoising autoencoder in Tensorflow

Tensorflow implementation of adversarial auto-encoder for MNIST

Learning deep representations by mutual information estimation and maximization

State Representation Learning (SRL) zoo with PyTorch - Part of S-RL Toolbox

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

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)

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

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.

Theano implementation of Sequence-to-Sequence Autoencoder

A Variational Autoencoder (VAE) implemented in PyTorch

Anomaly detection for streaming data using autoencoders

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

Reference code for the paper: Deep White-Balance Editing, CVPR 2020 (Oral). Our method is a deep learning multi-task framework for white-balance editing.

Convolutional AutoEncoder application on MRI images

Library of autoencoders for sequential data

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

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

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

Focal Frequency Loss for Generative Models

Easy Reduced Basis method

PyTorch implementation of DEC (Deep Embedding Clustering)

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

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

Using Autoencoders for classification as unsupervised machine learning algorithms with Deep Learning.

Representation learning for link prediction within social networks

Deep Learning sample programs using PyTorch in C++

Dual CNN Models for Unsupervised Monocular Depth Estimation

Tensorflow implementation of Adversarial Autoencoders

Autoencoder trained on ImageNet Using Torch 7

Variational Recurrent Autoencoder for timeseries clustering in pytorch

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

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

Image reconstruction done with untrained neural networks.

Real time face landmarking using decision trees and NN autoencoders

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).

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

Visualization techniques for the latent space of a convolutional autoencoder in Keras

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

Generative Adversarial Networks and Autoencoders for 3D Shapes

Noise removal from images using Convolutional autoencoder

A simple Tensorflow based library for deep and/or denoising AutoEncoder.

This is the official implementation for the paper 'AutoEncoder by Forest'

Tensorflow implementation of conditional variational auto-encoder for MNIST

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…

Code & data accompanying the KDD 2017 paper "KATE: K-Competitive Autoencoder for Text"

Tensorflow 2.0 implementation of Adversarial Autoencoders

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

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

Deep learning meets molecular dynamics.

Integrated Cell project implemented in pytorch

Convolutional Autoencoder for Loop Closure

Deep learning image autoencoder that not depends on image resolution

🌐 Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization

Interactive Visual Machine Learning Demos.

Neural network library written in C and Javascript

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

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

A curated list of dedicated resources and applications