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awesome-differential-privacy

Differential privacy theory and code, differential private machine learning

awesome-differential-privacy-and-meachine-learning

机器学习和差分隐私的论文笔记和代码仓

backdoor_federated_learning

Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)

backdoors101

Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.

ben-decentralized-chatbot

YC Hackathon 2018 Winner Project. BEN: A decentralized chatbot that uses federated learning.

benedekrozemberczki-awesome-graph-classification

bigmartpredmodel

The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. The aim is to build a predictive model and find out the sales of each product at a particular store.Using this predictive model the data scientists at BigMart can understand the properties of products and stores which play a key role in increasing sales. The tasks done for this project are : *Data Exploration *Data QAQC *Outlier detection and missing data replacement strategy *Data ETL *Understanding about sales domain *Feature Engineering *Advanced Data Analysis *Regression modeling Techniques *Hybrid modeling Techniques *Specific measure to Evaluate Model ​ The datasets were acquired from : https://s3.amazonaws.com/hackerday.datascience/49/Test_u94Q5KV.csv https://s3.amazonaws.com/hackerday.datascience/49/Train_UWu5bXk.csv https://s3.amazonaws.com/hackerday.datascience/49/SampleSubmission_TmnO39y.csv Software Requirements : Continuum Analytics, Inc software Python 2.7 version with seaborn package was used.

bihad

blog

Some notes on things I find interesting and important.

cluster-gcn

基于pymetis的Cluster-GCN，参考自https://github.com/benedekrozemberczki/ClusterGCN，略作修改

conv-emotion

This repo contains implementation of different architectures for emotion recognition in conversations.

datapoisoning_fl

Code for Data Poisoning Attacks Against Federated Learning Systems

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

differential-privacy-vs-fairness

Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19

dimensionality_reduction_alo_codes

特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现

evaluatingdpml

This project's goal is to evaluate the privacy leakage of differentially private machine learning models.

federated-learning

A Keras implementation of FederatedAvergaing [McMahan, Brendan, et al. 2017] and Lazily Aggregated Stochastic Gradients [Chen, Tianyi, Yuejiao Sun, and Wotao Yin. 2020]

federated-learning-1

联邦学习

federated-learning-pytorch

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

gnn-meta-attack

Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".

gnn4nlp-papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

grand

Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"

graph-representation-learning

Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)

graphembedding

Implementation and experiments of graph embedding algorithms.deep walk,LINE(Large-scale Information Network Embedding),node2vec,SDNE(Structural Deep Network Embedding),struc2vec

gxn

Graph Cross Network

netgan

Implementation of the paper "NetGAN: Generating Graphs via Random Walks".

nettack

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

nlp_paper_study

研读顶会论文，复现论文相关代码

pgl

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

planetoid

Semi-supervised learning with graph embeddings