142 Open source projects that are alternatives of or similar to peax

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

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

Integrated Cell project implemented in pytorch

Image reconstruction done with untrained neural networks.

Deep Learning sample programs using PyTorch in C++

Easy Reduced Basis method

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

Real time face landmarking using decision trees and NN autoencoders

Deep learning meets molecular dynamics.

Representation learning for link prediction within social networks

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R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

Predicting regulatory DNA elements based on epigenomic signatures

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

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

Generative Adversarial Networks and Autoencoders for 3D Shapes

Theano implementation of Sequence-to-Sequence Autoencoder

Tensorflow implementation of conditional variational auto-encoder for MNIST

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

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

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

Convolutional Autoencoder for Loop Closure

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

Autoencoders in Keras

Tensorflow implementation of Adversarial Autoencoders

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.

Structural Deep Clustering Network

Tensorflow implementation of adversarial auto-encoder for MNIST

中文的 tensorflow tutorial with jupyter notebooks

Bead-based single-cell atac processing

Library of autoencoders for sequential data

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

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

Dual CNN Models for Unsupervised Monocular Depth Estimation

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

Tensorflow 2.0 implementation of Adversarial Autoencoders

Implementation of the stacked denoising autoencoder in Tensorflow

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

Focal Frequency Loss for Generative Models

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

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

Deep learning image autoencoder that not depends on image resolution

PyTorch implementation of DEC (Deep Embedding Clustering)

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

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

AnaLysis routines for ePigenomicS data - 🏫 Bioconductor project

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

A curated list of dedicated resources and applications

Anomaly detection for streaming data using autoencoders

Interactive Neural Machine Translation tool

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

A Variational Autoencoder (VAE) implemented in PyTorch

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Real-time Recognition of german sign language (DGS) with MediaPipe

Learning deep representations by mutual information estimation and maximization

Haystack: Epigenetic Variability and Transcription Factor Motifs Analysis Pipeline

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

RootPainter: Deep Learning Segmentation of Biological Images with Corrective Annotation

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

Variational Recurrent Autoencoder for timeseries clustering in pytorch