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

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

This repo includes the source code of the fully convolutional depth denoising model presented in https://arxiv.org/pdf/1909.01193.pdf (ICCV19)

Frame level anomaly detection and localization in videos using auto-encoders

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.

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

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The hybrid model combining stacked denoising autoencoder with matrix factorization is applied, to predict the customer purchase behavior in the future month according to the purchase history and user information in the Santander dataset.

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…

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

Large scale training of factorization models for Collaborative Filtering with PyTorch

Deep learning meets molecular dynamics.

Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

Using Deep Autoencoders for predictions of movie ratings.

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

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

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

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[CVPR2020] Adversarial Latent Autoencoders

PyTorch implementation of SDAE (Stacked Denoising AutoEncoder)

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

Autoencoders using Keras

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.

several basic neural networks[mlp, autoencoder, CNNs, recurrentNN, recursiveNN] implements under several NN frameworks[ tensorflow, pytorch, theano, keras]

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

Structural Deep Clustering Network

Variational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"

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

Automatic Feature Generation for Website Fingerprinting

Tensorflow implementation : U-net and FCN with global convolution

Advanced Deep Learning with Keras, published by Packt

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

Next RecSys Library

A Pytorch implementation for the ZeroSpeech 2019 challenge.

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.

Focal Frequency Loss for Generative Models

DanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)

PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Anomaly detection for streaming data using autoencoders

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Keras implementation of Structural Deep Network Embedding, KDD 2016

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PyTorch implementation of DEC (Deep Embedding Clustering)

Autoencoder for Point Clouds

Use unsupervised and supervised learning to predict stocks

Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow

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

Tensorflow implementation of conditional variational auto-encoder for MNIST

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Autoencoders in Keras

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