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Privacy Preserving

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/vikasverma1077/GraphMix

공식 코드

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

https://github.com/vincentx15/rnattentional

공식 코드

Edge-similarity-aware Graph Neural Networks

https://github.com/vinhsuhi/wge

공식 코드

Two-view Graph Neural Networks for Knowledge Graph Completion

https://github.com/vinuni-vishc/pppf-cross-silo-fl

공식 코드

Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning

https://github.com/visdata/geneticflow

공식 코드

Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs

https://github.com/visym/keynet

공식 코드

Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision Sensors

https://github.com/vita-group/dp-opt

공식 코드

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

https://github.com/vitae-transformer/p3m-net

공식 코드

Rethinking Portrait Matting with Privacy Preserving

https://github.com/viz27/secomm

공식 코드

Unsupervised Constrained Community Detection via Self-Expressive Graph Neural Network

https://github.com/vmart20/PieCoN

공식 코드

Piecewise Constant Spectral Graph Neural Network

https://github.com/vmtenorio/robust_gnn

공식 코드

Robust Graph Neural Network based on Graph Denoising

https://github.com/vothanhvinh/causalfi

공식 코드

Federated Causal Inference from Observational Data

https://github.com/vothanhvinh/causalrff

공식 코드

Federated Causal Inference from Observational Data

https://github.com/vothanhvinh/fedci

공식 코드

Federated Causal Inference from Observational Data

https://github.com/vperifan/federated-time-series-forecasting

공식 코드

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting

https://github.com/vpsg-research/waveguard

공식 코드

WaveGuard: Robust Deepfake Detection and Source Tracing via Dual-Tree Complex Wavelet and Graph Neural Networks

https://github.com/vt-asaplab/vPIN

공식 코드

Privacy-Preserving Verifiable Neural Network Inference Service

https://github.com/vthost/DAGNN

공식 코드

Directed Acyclic Graph Neural Networks

https://github.com/vvarga90/gnn_annot

공식 코드

Fast Interactive Video Object Segmentation with Graph Neural Networks

https://github.com/waimorris/E-GraphSAGE

공식 코드

E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT

https://github.com/walidgeuttala/Synthetic-Benchmark-for-Graph-Classification

공식 코드

On the Power of Graph Neural Networks and Feature Augmentation Strategies to Classify Social Networks

https://github.com/walkieq/gnn-jedinet-fpga

공식 코드

LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy Physics

https://github.com/wangcunxiang/graph-as-tokens

공식 코드

Exploiting Abstract Meaning Representation for Open-Domain Question Answering

https://github.com/wangjs96/graph-in-graph-neural-network

공식 코드

Graph in Graph Neural Network

https://github.com/wangxfng/nfarec

공식 코드

NFARec: A Negative Feedback-Aware Recommender Model

https://github.com/wangyifeibeijing/user

공식 코드

USER: Unsupervised Structural Entropy-based Robust Graph Neural Network

https://github.com/wangyixinxin/dagi

공식 코드

Imputing Brain Measurements Across Data Sets via Graph Neural Networks

https://github.com/wangyu0627/gc-hgnn

공식 코드

Generative-Contrastive Heterogeneous Graph Neural Network

https://github.com/warisgill/FedDefender

공식 코드

FedDefender: Backdoor Attack Defense in Federated Learning

https://github.com/warisgill/tracefl

공식 코드

TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance

https://github.com/wayfear/brainnetworktransformer

공식 코드

MHNet: Multi-view High-order Network for Diagnosing Neurodevelopmental Disorders Using Resting-state fMRI

https://github.com/wayfear/fbnetgen

공식 코드

FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation

https://github.com/wdimmy/graphretrieval

공식 코드

An Empirical Study of Retrieval-enhanced Graph Neural Networks

https://github.com/wdvorkin/syntheticdata

공식 코드

Differentially Private Algorithms for Synthetic Power System Datasets

https://github.com/webis-de/archive-query-log

공식 코드

The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives

https://github.com/webis-de/sigir-23

공식 코드

The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.