Papers with Code 아카이브

Privacy Preserving

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

https://github.com/fhendriks11/simegnn

공식 코드

Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials

https://github.com/filippomb/simplifying-clustering-with-graph-neural-networks

공식 코드

Simplifying Clustering with Graph Neural Networks

https://github.com/finint/THGNN

공식 코드

Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction

https://github.com/finint/antifraud

공식 코드

Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation

https://github.com/firasgit/medicaldiffusion

공식 코드

Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation

https://github.com/fishmingyu/geot

공식 코드

GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU

https://github.com/fishmoon1234/DAG-GNN

공식 코드

DAG-GNN: DAG Structure Learning with Graph Neural Networks

https://github.com/flamezz5201/disgnet

공식 코드

DisGNet: A Distance Graph Neural Network for Forward Kinematics Learning of Gough-Stewart Platform

https://github.com/fleecermw/privacyfedllm

공식 코드

Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix

https://github.com/floklimm/graphon

공식 코드

Modularity maximisation for graphons

https://github.com/floriangroetschla/core-gd

공식 코드

CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs

https://github.com/flyingdoog/PGExplainer

공식 코드

Parameterized Explainer for Graph Neural Network

https://github.com/forget2save/campro

공식 코드

CamPro: Camera-based Anti-Facial Recognition

https://github.com/francescodisalvo05/cvae-anonymization

공식 코드

Privacy-preserving datasets by capturing feature distributions with Conditional VAEs

https://github.com/francescoferrini/MPS-GNN

공식 코드

A Self-Explainable Heterogeneous GNN for Relational Deep Learning

https://github.com/franklinnwren/ds-age

공식 코드

Dissimilar Nodes Improve Graph Active Learning

https://github.com/fredjo89/heterogeneous-mpnn

공식 코드

Finding Money Launderers Using Heterogeneous Graph Neural Networks

https://github.com/freesunshine0316/dep-forest-re

공식 코드

Leveraging Dependency Forest for Neural Medical Relation Extraction

https://github.com/freesunshine0316/nary-grn

공식 코드

Tackling Graphical NLP problems with Graph Recurrent Networks

https://github.com/fshp971/RPG

공식 코드

Robustness, Privacy, and Generalization of Adversarial Training

https://github.com/fuankarion/end-to-end-asd

공식 코드

End-to-End Active Speaker Detection

https://github.com/fufangze/SDR-GNN

공식 코드

SDR-GNN: Spectral Domain Reconstruction Graph Neural Network for Incomplete Multimodal Learning in Conversational Emotion Recognition

https://github.com/fulifeng/GraphAT

공식 코드

Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure

https://github.com/fumiyukikato/fl-tee

공식 코드

OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification

https://github.com/funket/zorro

공식 코드

Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks

https://github.com/fushenghao/privacypreservingml

공식 코드

Human-imperceptible, Machine-recognizable Images

https://github.com/futianfan/clinical-trial-outcome-prediction

공식 코드

HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data

https://github.com/fuvty/DeSCo

공식 코드

DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting

https://github.com/fxsxjtu/grato

공식 코드

GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search

https://github.com/g2lab/pcfbl

공식 코드

Privacy-preserving patient clustering for personalized federated learning

https://github.com/garyjiajia/tsg

공식 코드

Transforming Visual Scene Graphs to Image Captions

https://github.com/gatech-eic/edge-llm

공식 코드

EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

https://github.com/gayanku/FDGATII

공식 코드

FDGATII : Fast Dynamic Graph Attention with Initial Residual and Identity Mapping

https://github.com/gbouritsas/graph-substructure-networks

공식 코드

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

https://github.com/gdasoulas/pgso

공식 코드

Learning Parametrised Graph Shift Operators

https://github.com/gdl-unive/histogram-intersection-kernel

공식 코드

GNN-LoFI: a Novel Graph Neural Network through Localized Feature-based Histogram Intersection

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