autoencoders 开源项目推荐（640 个）

serengil /tensorflow-101

TensorFlow 101：深度学习入门

curiousily /Deep-Learning-For-Hackers

使用Python中TensorFlow 2和Keras的机器学习教程（包含Jupyter笔记本）——（LSTMs、超参数调优、数据预处理、偏差-方差权衡、异常检测、自编码器、时间序列预测、目标检测、情感分析、基于BERT的意图识别）。

aapatel09 /handson-unsupervised-learning

《Hands-on Unsupervised Learning Using Python》（O'Reilly Media）配套代码

AutoViML /featurewiz

使用高级特征工程策略，并仅用一行代码从数据集中选择最佳特征。由 Ram Seshadri 创建。欢迎协作者。

curiousily /Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras

展示如何在 Keras 中构建深度自编码器以进行信用卡交易数据异常检测的 iPython notebook 和预训练模型

khanhnamle1994 /MetaRec

一系列基于深度学习的推荐模型的 PyTorch 实现

nathanhubens /Autoencoders

使用 Keras 实现简单自编码器网络

aqibsaeed /Place-Recognition-using-Autoencoders-and-NN

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

vuptran /graph-representation-learning

[DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification

CompVis /net2net

使用条件可逆神经网络进行网络到网络翻译

harveyslash /Deep-Steganography

Hiding Images within other images using Deep Learning

pcko1 /Deep-Drug-Coder

A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.

FutureXiang /ddae

[ICCV 2023 Oral] Official Implementation of "Denoising Diffusion Autoencoders are Unified Self-supervised Learners"

alexandru-dinu /cae

Compressive AutoEncoder.

jbramburger /DataDrivenDynSyst

用于书籍《基于数据的动态系统方法》的脚本和笔记本

milaan9 /Deep_Learning_Algorithms_from_Scratch

This repository explores the variety of techniques and algorithms commonly used in deep learning and the implementation in MATLAB and PYTHON

numaproj /numalogic

Collection of operational time series ML models and tools

yinboc /dito

Official PyTorch Implementation of "Diffusion Autoencoders are Scalable Image Tokenizers"

cwkx /GON

Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder

rezacsedu /Deep-Learning-for-Clustering-in-Bioinformatics

Deep Learning-based Clustering Approaches for Bioinformatics