Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Overview

Awesome-Federated-Learning-on-Graph-and-GNN-papers

federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Federated Learning on Graphs

  1. [Arxiv 2019] Peer-to-peer federated learning on graphs. paper
  2. [NeurIPS Workshop 2019] Towards Federated Graph Learning for Collaborative Financial Crimes Detection. paper
  3. [Arxiv 2021] A Graph Federated Architecture with Privacy Preserving Learning. paper
  4. [Arxiv 2021] Federated Myopic Community Detection with One-shot Communication. paper

Federated Learning on Graph Neural Networks

Survey Papers

  1. [Arxiv 2021] FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. paper
  2. [Arxiv 2021] Federated Graph Learning -- A Position Paper. paper

Algorithm Papers

  1. [Arxiv 2020] Federated Dynamic GNN with Secure Aggregation. paper
  2. [Arxiv 2020] Privacy-Preserving Graph Neural Network for Node Classification. paper
  3. [Arxiv 2020] ASFGNN: Automated Separated-Federated Graph Neural Network. paper
  4. [Arxiv 2020] GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs. paper
  5. [Arxiv 2021] FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation. paper
  6. [ICLR-DPML 2021] FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. paper code
  7. [Arxiv 2021] FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search. paper
  8. [CVPR 2021] Cluster-driven Graph Federated Learning over Multiple Domains. paper
  9. [Arxiv 2021] FedGL: Federated Graph Learning Framework with Global Self-Supervision. paper
  10. [AAAI 2022] SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks. paper
  11. [KDD 2021] Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling. paper code
  12. [Arxiv 2021] A Vertical Federated Learning Framework for Graph Convolutional Network. paper
  13. [NeurIPS 2021] Federated Graph Classification over Non-IID Graphs. paper
  14. [NeurIPS 2021] Subgraph Federated Learning with Missing Neighbor Generation. paper
  15. [CIKM 2021] Differentially Private Federated Knowledge Graphs Embedding. paper code
  16. [MICCAI Workshop 2021] A Federated Multigraph Integration Approach for Connectional Brain Template Learning. paper
  17. [TPDS 2021] FedGraph: Federated Graph Learning with Intelligent Sampling. paper

Federated Learning on Knowledge Graph

  1. [Arxiv 2020] FedE: Embedding Knowledge Graphs in Federated Setting. paper code
  2. [Arxiv 2020] Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty. paper
  3. [CIKM 2021] Federated Knowledge Graphs Embedding.paper
  4. [Arxiv 2021] Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries. paper

Private Graph Neural Networks

  1. [IEEE Big Data 2019] A Graph Neural Network Based Federated Learning Approach by Hiding Structure. paper
  2. [Arxiv 2020] Locally Private Graph Neural Networks. paper
  3. [Arxiv 2021] Privacy-Preserving Graph Convolutional Networks for Text Classification. paper
  4. [Arxiv 2021] GraphMI: Extracting Private Graph Data from Graph Neural Networks. paper
  5. [Arxiv 2021] Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning. paper

Federated Learning: Survey

  1. [IEEE Signal Processing Magazine 2019] Federated Learning:Challenges, Methods, and Future Directions. paper
  2. [ACM TIST 2019] Federated Machine Learning Concept and Applications. paper
  3. [IEEE Communications Surveys & Tutorials 2020] Federated Learning in Mobile Edge Networks A Comprehensive Survey. paper

Graph Neural Networks: Survey

  1. [IEEE TNNLS 2020] A Comprehensive Survey on Graph Neural Networks. paper
  2. [IEEE TKDE 2020] Deep Learning on Graphs: A Survey. paper
  3. [AI Open] Graph Neural Networks: A Review of Methods and Applications. paper
  4. [ArXiv 2021] Graph Neural Networks in Network Neuroscience. paper -- GitHub repo of all reviewed papers
Owner
keven
keven
Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".

Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".

Xiangyin Kong 7 Nov 08, 2022
Official repository for ABC-GAN

ABC-GAN The work represented in this repository is the result of a 14 week semesterthesis on photo-realistic image generation using generative adversa

IgorSusmelj 10 Jun 23, 2022
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Zhiqiang Shen 52 Dec 24, 2022
Project page of the paper 'Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network' (ECCVW 2018)

EPSR (Enhanced Perceptual Super-resolution Network) paper This repo provides the test code, pretrained models, and results on benchmark datasets of ou

Subeesh Vasu 78 Nov 19, 2022
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A

Piotr Migdał 1.2k Jan 08, 2023
Face recognize and crop them

Face Recognize Cropping Module Source 아이디어 Face Alignment with OpenCV and Python Requirement 필요 라이브러리 imutil dlib python-opence (cv2) Usage 사용 방법 open

Cho Moon Gi 1 Feb 15, 2022
This is a repository of our model for weakly-supervised video dense anticipation.

Introduction This is a repository of our model for weakly-supervised video dense anticipation. More results on GTEA, Epic-Kitchens etc. will come soon

2 Apr 09, 2022
A task Provided by A respective Artenal Ai and Ml based Company to complete it

A task Provided by A respective Alternal Ai and Ml based Company to complete it .

Parth Madan 1 Jan 25, 2022
Codes and Data Processing Files for our paper.

Code Scripts and Processing Files for EEG Sleep Staging Paper 1. Folder Tree ./src_preprocess (data preprocessing files for SHHS and Sleep EDF) sleepE

Chaoqi Yang 18 Dec 12, 2022
Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling This repo contains the official implementation for the paper On Path Int

Ruiqi Gao 39 Nov 10, 2022
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks

Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec

19 Nov 30, 2022
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http

chenm 253 Dec 08, 2022
A CNN implementation using only numpy. Supports multidimensional images, stride, etc.

A CNN implementation using only numpy. Supports multidimensional images, stride, etc. Speed up due to heavy use of slicing and mathematical simplification..

2 Nov 30, 2021
Fully-automated scripts for collecting AI-related papers

AI-Paper-collector Fully-automated scripts for collecting AI-related papers List of Conferences to crawel ACL: 21-19 (including findings) EMNLP: 21-19

Gordon Lee 776 Jan 08, 2023
HGCN: Harmonic Gated Compensation Network For Speech Enhancement

HGCN The official repo of "HGCN: Harmonic Gated Compensation Network For Speech Enhancement", which was accepted at ICASSP2022. How to use step1: Calc

ScorpioMiku 33 Nov 14, 2022
AbelNN: Deep Learning Python module from scratch

AbelNN: Deep Learning Python module from scratch I have implemented several neural networks from scratch using only Numpy. I have designed the module

Abel 2 Apr 12, 2022
SelfAugment extends MoCo to include automatic unsupervised augmentation selection.

SelfAugment extends MoCo to include automatic unsupervised augmentation selection. In addition, we've included the ability to pretrain on several new datasets and included a wandb integration.

Colorado Reed 24 Oct 26, 2022
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space

Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte

38 Dec 15, 2022
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer

CSAW-M This repository contains code for CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer. Source code for tr

Yue Liu 7 Oct 11, 2022
Flexible time series feature extraction & processing

tsflex is a toolkit for flexible time series processing & feature extraction, that is efficient and makes few assumptions about sequence data. Useful

PreDiCT.IDLab 206 Dec 28, 2022