Keras Idiomatic ProgrammerBooks, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Ad examplesA 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.
Tensorflow BookAccompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
DancenetDanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)
PyodA Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Generative ModelsAnnotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
AutoencodersTorch implementations of various types of autoencoders
Deepsvg[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.
ZhihuThis 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.
Alae[CVPR2020] Adversarial Latent Autoencoders
Noise2Noise-audio denoising without clean training dataSource 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…
Cifar-AutoencoderA look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.
T3[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
SAE-NADThe implementation of "Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence"
video autoencoderVideo lstm auto encoder built with pytorch. https://arxiv.org/pdf/1502.04681.pdf
AE-CNNICVGIP' 18 Oral Paper - Classification of thoracic diseases on ChestX-Ray14 dataset
mirapyMiraPy: A Python package for Deep Learning in Astronomy
sldm4-h2oStatistical Learning & Data Mining IV - H2O Presenation & Tutorial
AutoEncodersVariational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras
abae-pytorchPyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'
TensorFlow-AutoencodersImplementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder
haskell-vaeLearning about Haskell with Variational Autoencoders
Encoder-ForesteForest: Reversible mapping between high-dimensional data and path rule identifiers using trees embedding
deep-stegGlobal NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"
autoencoder for physical layerThis 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
VisualMLInteractive Visual Machine Learning Demos.
catseyeNeural network library written in C and Javascript
mauiMulti-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit
seq3Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"
SESF-FuseSESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion
Video-Compression-NetA 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…
peaxPeax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
topological-autoencodersCode for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
GATEThe implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"
probabilistic nlgTensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).
Face-LandmarkingReal time face landmarking using decision trees and NN autoencoders
dltfHands-on in-person workshop for Deep Learning with TensorFlow