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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/huankoh/cst-gl

공식 코드

Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection

https://github.com/hugochan/GraphFlow

공식 코드

GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension

https://github.com/hugochan/RL-based-Graph2Seq-for-NQG

공식 코드

Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation

https://github.com/hugoschnoering2/BTCGraphLabeling

공식 코드

Bitcoin Research with a Transaction Graph Dataset

https://github.com/hui-po-wang/fedlap-dp

공식 코드

FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations

https://github.com/huilinchenjn/upc_sdg

공식 코드

Privacy-Preserving Synthetic Data Generation for Recommendation Systems

https://github.com/huiminzeng/gpt-fedrec

공식 코드

Federated Recommendation via Hybrid Retrieval Augmented Generation

https://github.com/hukkelas/deep_privacy2

공식 코드

Does Image Anonymization Impact Computer Vision Training?

https://github.com/human-analysis/diverse3dface

공식 코드

Generating Diverse 3D Reconstructions from a Single Occluded Face Image

https://github.com/humblef-oo-l/DP

공식 코드

Reconciling Privacy and Explainability in High-Stakes: A Systematic Inquiry

https://github.com/hust-eic-ai-lab/ucadi

공식 코드

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence

https://github.com/hwang52/fedsc

공식 코드

FedSC: Federated Learning with Semantic-Aware Collaboration

https://github.com/hwang52/fedskc

공식 코드

FedSKC: Federated Learning with Non-IID Data via Structural Knowledge Collaboration

https://github.com/hxttkl/GraphAdapter

공식 코드

Can GNN be Good Adapter for LLMs?

https://github.com/hyeonahkimm/neuralsep

공식 코드

A Neural Separation Algorithm for the Rounded Capacity Inequalities

https://github.com/hyeonsoojo/metagc

공식 코드

Robust Graph Clustering via Meta Weighting for Noisy Graphs

https://github.com/hysonlab/multiscalehsi

공식 코드

MOB-GCN: A Novel Multiscale Object-Based Graph Neural Network for Hyperspectral Image Classification

https://github.com/hysonlab/tesgraph

공식 코드

TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scene Understanding

https://github.com/iRxyzzz/nn-emd

공식 코드

NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-Sourced Datasets

https://github.com/iarai/mets-10

공식 코드

Metropolitan Segment Traffic Speeds from Massive Floating Car Data in 10 Cities

https://github.com/iarai/neurips2022-traffic4cast

공식 코드

Multi-task Learning for Sparse Traffic Forecasting

https://github.com/ichn-hu/Parsing-Obfuscation

공식 코드

Obfuscation for Privacy-preserving Syntactic Parsing

https://github.com/icon-lab/FedGAT

공식 코드

Generative Autoregressive Transformers for Model-Agnostic Federated MRI Reconstruction

https://github.com/ict-gimlab/sehgnn

공식 코드

Simple and Efficient Heterogeneous Graph Neural Network

https://github.com/idc-neu/neutronbench

공식 코드

Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective

https://github.com/idea-iitd/GraphReach

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GraphReach: Position-Aware Graph Neural Network using Reachability Estimations

https://github.com/idea-iitd/greed

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GREED: A Neural Framework for Learning Graph Distance Functions

https://github.com/idea-iitd/neurocut

공식 코드

NeuroCUT: A Neural Approach for Robust Graph Partitioning

https://github.com/idea-iitd/neurosed

공식 코드

GREED: A Neural Framework for Learning Graph Distance Functions

https://github.com/ifm-mag/HyDRO_PLUS

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Efficient and Privacy-Preserved Link Prediction via Condensed Graphs

https://github.com/iit-pavis/diffassemble

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DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly

https://github.com/iit-pavis/posernet

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PoserNet: Refining Relative Camera Poses Exploiting Object Detections

https://github.com/ilayluz/learning-amg

공식 코드

Learning Algebraic Multigrid Using Graph Neural Networks

https://github.com/illidanlab/hyfl

공식 코드

A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection

https://github.com/ilyaorson/cyberdreamcatcher

공식 코드

An Attentive Graph Agent for Topology-Adaptive Cyber Defence

https://github.com/imatge-upc/CartNet

공식 코드

A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation

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