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Privacy Preserving

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

https://github.com/Microsoft/PDP-Solver

공식 코드

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

https://github.com/MikeZChi/GSPHAR

공식 코드

Graph Signal Processing for Global Stock Market Realized Volatility Forecasting

https://github.com/Mitan/po-gp-ucb

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Private Outsourced Bayesian Optimization

https://github.com/Mobzhang/PT-DGNN

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Pre-Training on Dynamic Graph Neural Networks

https://github.com/MountainChenCad/HRRPGraphNet

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HRRPGraphNet: Make HRRPs to Be Graphs for Efficient Target Recognition

https://github.com/MrVPlusOne/LambdaNet

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LambdaNet: Probabilistic Type Inference using Graph Neural Networks

https://github.com/MysteryVaibhav/fake_news_semantics

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Do Sentence Interactions Matter? Leveraging Sentence Level Representations for Fake News Classification

https://github.com/NAVER-INTEL-Co-Lab/gaudi-fl

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Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks

https://github.com/NIPS2019-authors/MoLe_public

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Towards Efficient and Secure Delivery of Data for Training and Inference with Privacy-Preserving

https://github.com/NSLab-CUK/S-CGIB

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Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

https://github.com/NYUMedML/GNN_for_EHR

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Variationally Regularized Graph-based Representation Learning for Electronic Health Records

https://github.com/Nanyuu/TUA

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A Targeted Universal Attack on Graph Convolutional Network

https://github.com/NiklasFreymuth/AMBER

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Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations

https://github.com/Nokia-Bell-Labs/olp-gnn

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Learning Optimal Linear Precoding for Cell-Free Massive MIMO with GNN

https://github.com/NormXU/Layout2Graph

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PARAGRAPH2GRAPH: A GNN-based framework for layout paragraph analysis

https://github.com/OTTO-OTO/SCARA-Semi-Open

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Position: On-Premises LLM Deployment Demands a Middle Path: Preserving Privacy Without Sacrificing Model Confidentiality

https://github.com/Open-Catalyst-Project/Open-Catalyst-Dataset

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The Open Catalyst 2020 (OC20) Dataset and Community Challenges

https://github.com/Open-Catalyst-Project/ocp

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The Open Catalyst 2020 (OC20) Dataset and Community Challenges

https://github.com/OpenImagingLab/LenslessFace

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LenslessFace: An End-to-End Optimized Lensless System for Privacy-Preserving Face Verification

https://github.com/OpenMined/PSI

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Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning

https://github.com/OpenMined/PyDentity/tree/master/projects/aries-fl

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Privacy and Trust Redefined in Federated Machine Learning

https://github.com/OpenMined/PySyft

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Syft 0.5: A Platform for Universally Deployable Structured Transparency

https://github.com/OpenMined/PyVertical

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Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning

https://github.com/OpenMined/TenSEAL

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TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption

https://github.com/Optimization-and-Machine-Learning-Lab/energy_fed_trpo

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Generalizing in Net-Zero Microgrids: A Study with Federated PPO and TRPO

https://github.com/PASSIONLab/CAGNET

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Reducing Communication in Graph Neural Network Training

https://github.com/PASSIONLab/gnn_training

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Reducing Communication in Graph Neural Network Training

https://github.com/PIK-ICoNe/DBGNN_paper-companion

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Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions

https://github.com/PKUDigitalHealth/KidneyTalk-open

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KidneyTalk-open: No-code Deployment of a Private Large Language Model with Medical Documentation-Enhanced Knowledge Database for Kidney Disease

https://github.com/PPMTF/PPMTF

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Privacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific Features

https://github.com/PaddlePaddle/PGL

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Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems

https://github.com/PaddlePaddle/PGL/tree/main/ogb_examples/nodeproppred/unimp

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Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/SEENet

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Multi-Temporal Relationship Inference in Urban Areas

https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/SHGNN

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Spatial Heterophily Aware Graph Neural Networks

https://github.com/ParkLabML/DP-MERF

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DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation

https://github.com/PengBoXiangShang/multigraph_transformer

공식 코드

Multi-Graph Transformer for Free-Hand Sketch Recognition

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