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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/mie-lab/ckg-traffic-forecasting

공식 코드

Context-aware knowledge graph framework for traffic speed forecasting using graph neural network

https://github.com/mieskolainen/hypertrack

공식 코드

HyperTrack: Neural Combinatorics for High Energy Physics

https://github.com/mikezchi/dcrnn-rv

공식 코드

Global Stock Market Volatility Forecasting Incorporating Dynamic Graphs and All Trading Days

https://github.com/mims-harvard/gnndelete

공식 코드

GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

https://github.com/mingchenli/MCGEN-Private-Synthetic-Data-Generator

공식 코드

MC-GEN:Multi-level Clustering for Private Synthetic Data Generation

https://github.com/mingliangzhang2018/PGDP

공식 코드

Plane Geometry Diagram Parsing

https://github.com/mingzhe-han/fedcia

공식 코드

FedCIA: Federated Collaborative Information Aggregation for Privacy-Preserving Recommendation

https://github.com/miracle-2001/gnn4eeg

공식 코드

GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network

https://github.com/mirjanic/nar-latent-spaces

공식 코드

Latent Space Representations of Neural Algorithmic Reasoners

https://github.com/mit-han-lab/offsite-tuning

공식 코드

Offsite-Tuning: Transfer Learning without Full Model

https://github.com/mit-tesse/dsg-rl

공식 코드

Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs using Graph Neural Networks

https://github.com/mkhodak/private-quantiles

공식 코드

Learning-Augmented Private Algorithms for Multiple Quantile Release

https://github.com/mklab-iti/decentralized-gnn

공식 코드

p2pGNN: A Decentralized Graph Neural Network for Node Classification in Peer-to-Peer Networks

https://github.com/ml-postech/reverse-gnn

공식 코드

Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs

https://github.com/ml4bio/ribodiffusion

공식 코드

RiboDiffusion: Tertiary Structure-based RNA Inverse Folding with Generative Diffusion Models

https://github.com/ml4sci/qmlhep

공식 코드

Lie-Equivariant Quantum Graph Neural Networks

https://github.com/mlc-ai/web-llm

공식 코드

WebLLM: A High-Performance In-Browser LLM Inference Engine

https://github.com/mlvlab/SELAR

공식 코드

Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning

https://github.com/mmalekzadeh/motion-sense

공식 코드

Protecting Sensory Data against Sensitive Inferences

https://github.com/mmalekzadeh/privacy-preserving-bandits

공식 코드

Privacy-Preserving Bandits

https://github.com/mmalekzadeh/replacement-autoencoder

공식 코드

Replacement AutoEncoder: A Privacy-Preserving Algorithm for Sensory Data Analysis

https://github.com/mmalekzadeh/vicious-classifiers

공식 코드

Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge Computing

https://github.com/mmendiet/fedalign

공식 코드

Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning

https://github.com/mocherson/Exp_GNN

공식 코드

Towards Expressive Graph Representation

https://github.com/mocherson/MedGCN

공식 코드

MedGCN: Medication recommendation and lab test imputation via graph convolutional networks

https://github.com/moe-zbeeb/exploring-the-landscape-for-generative-models-for-specialized-data-generation

공식 코드

Exploring the Landscape for Generative Sequence Models for Specialized Data Synthesis

https://github.com/mofanv/PPFL

공식 코드

PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments

https://github.com/mohbattharani/GVdoc

공식 코드

GVdoc: Graph-based Visual Document Classification

https://github.com/mojave-pku/TextLevelGCN

공식 코드

Text Level Graph Neural Network for Text Classification

https://github.com/mstubbemann/lg4av

공식 코드

LG4AV: Combining Language Models and Graph Neural Networks for Author Verification

https://github.com/mtandhj/sevo

공식 코드

Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution

https://github.com/mtics/feddae

공식 코드

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach

https://github.com/mtran14/dp_w2v2

공식 코드

A Speech Representation Anonymization Framework via Selective Noise Perturbation

https://github.com/muclover/pvcnn

공식 코드

pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing

https://github.com/mudit-dhawan/game-on

공식 코드

GAME-ON: Graph Attention Network based Multimodal Fusion for Fake News Detection

https://github.com/muhangtian/timediff

공식 코드

Reliable Generation of Privacy-preserving Synthetic Electronic Health Record Time Series via Diffusion Models

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