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

PyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'

This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

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

ICVGIP' 18 Oral Paper - Classification of thoracic diseases on ChestX-Ray14 dataset

Neural network library written in C and Javascript

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Experiments with Adversarial Autoencoders using Keras

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

Colorizing B&W Photos with Neural Networks

[CVPR2020] Adversarial Latent Autoencoders

The implementation of "Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence"

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

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

Statistical Learning & Data Mining IV - H2O Presenation & Tutorial

📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈

Tensorflow implementation of variational auto-encoder for MNIST

AE and VAE Playground in PyTorch

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

Global NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"

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.

Interactive Visual Machine Learning Demos.

TensorFlow and Deep Learning Tutorials

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

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…

[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

Autoencoder trained on ImageNet Using Torch 7

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.

Video lstm auto encoder built with pytorch. https://arxiv.org/pdf/1502.04681.pdf

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

MiraPy: A Python package for Deep Learning in Astronomy

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

Variational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras

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

Implementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder

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

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Automatic Feature Generation for Website Fingerprinting

Learning about Haskell with Variational Autoencoders

Torch implementations of various types of autoencoders

eForest: Reversible mapping between high-dimensional data and path rule identifiers using trees embedding

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

Shared Latent Space VAE's

[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.

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

Advanced Deep Learning with Keras, published by Packt

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

Autoencoder for Point Clouds

Noise removal from images using Convolutional autoencoder

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

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

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

Next RecSys Library

Autoencoders using Keras

Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf)

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.

Large scale training of factorization models for Collaborative Filtering with PyTorch

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

A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.