My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

Tensorflow implementation of variational auto-encoder for MNIST

Implementation of the stacked denoising autoencoder in Tensorflow

Tensorflow implementation of conditional variational auto-encoder for MNIST

The code for the MaD TwinNet. Demo page:

This repository tries to provide unsupervised deep learning models with Pytorch

Official implementation of pre-training via denoising for TorchMD-NET

Finding Direction of arrival (DOA) of small UAVs using Sparse Denoising Autoencoders and Deep Neural Networks.

Auto Encoders in PyTorch

Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016

Pytorch implementation of various autoencoders (contractive, denoising, convolutional, randomized)

Paper Detecting anomalous events in videos by learning deep representations of appearance and motion on python, opencv and tensorflow. This paper uses the stacked denoising autoencoder for the the feature training on the appearance and motion flow features as input for different window size and using multiple SVM as a single c

Medical Imaging, Denoising Autoencoder, Sparse Denoising Autoencoder (SDAE) End-to-end and Layer Wise Pretraining

A demo shows how to combine Langevin dynamics with score matching for generative models.

Denoising images with a Deep Convolutional Autoencoder - Implemented in Keras

kaggleのporto-seguro-safe-driver-prediction, michaelのsolver

Undergraduate research by Yuzhe Lim in Spring 2019. Field of research: Deep Neural Networks application on NILM (Nonintrusive load monitoring) for Energy Disaggregation

An implementation of Denoising Variational AutoEncoder with Topological loss

[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields

DDAE speech enhancement on spectrogram domain using Keras