Papers with Code 아카이브

Graph Neural Network

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

1

코드

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

https://github.com/BingJiaChen/few-shot-indoor-localization

공식 코드

Few-Shot Transfer Learning for Device-Free Fingerprinting Indoor Localization

https://github.com/BioinfoMachineLearning/DeepRefine

공식 코드

EGR: Equivariant Graph Refinement and Assessment of 3D Protein Complex Structures

https://github.com/CIAM-Group/NCO_code/tree/main/single_objective/UDC-Large-scale-CO-master

공식 코드

UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems

https://github.com/CODE-SUBMIT/Graph_Neighborhood_1

공식 코드

Mutual Information Maximization in Graph Neural Networks

https://github.com/CODE-SUBMIT/Neighborhood-Enlargement-in-Graph-Network

공식 코드

Mutual Information Maximization in Graph Neural Networks

https://github.com/COMPiLELab/SubDEQ

공식 코드

Subhomogeneous Deep Equilibrium Models

https://github.com/CRIPAC-DIG/A-PGNN

공식 코드

Personalized Graph Neural Networks with Attention Mechanism for Session-Aware Recommendation

https://github.com/CRIPAC-DIG/TAGNN

공식 코드

TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation

https://github.com/CaoQi92/CoupledGNN

공식 코드

Popularity Prediction on Social Platforms with Coupled Graph Neural Networks

https://github.com/CederGroupHub/chgnet

공식 코드

CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling

https://github.com/ChandlerBang/Pro-GNN

공식 코드

Graph Structure Learning for Robust Graph Neural Networks

https://github.com/Chen-Cai-OSU/GNN-Over-Smoothing

공식 코드

A Note on Over-Smoothing for Graph Neural Networks

https://github.com/Cra2yDavid/Powerformer

공식 코드

Powerformer: A Section-adaptive Transformer for Power Flow Adjustment

https://github.com/CrawlScript/RpHGNN

공식 코드

Efficient Heterogeneous Graph Learning via Random Projection

https://github.com/DSE-MSU/DeepRobust

공식 코드

Graph Structure Learning for Robust Graph Neural Networks

https://github.com/DanieleGammelli/gnn-rl-for-amod

공식 코드

Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems

https://github.com/DavideBuffelli/CliquePH

공식 코드

CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs

https://github.com/DavideScassola/graph-conditional-flow-matching

공식 코드

Graph Conditional Flow Matching for Relational Data Generation

https://github.com/Deceptrax123/LGIN

공식 코드

LGIN: Defining an Approximately Powerful Hyperbolic GNN

https://github.com/DeepGraphLearning/GNN-QE

공식 코드

Neural-Symbolic Models for Logical Queries on Knowledge Graphs

https://github.com/DeepGraphLearning/NBFNet

공식 코드

Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction

https://github.com/DennisCraandijk/DL-Abstract-Argumentation

공식 코드

Deep Learning for Abstract Argumentation Semantics

https://github.com/DevSinghSachan/syntax-augmented-bert

공식 코드

Do Syntax Trees Help Pre-trained Transformers Extract Information?

https://github.com/Drone-Banks/DICER-WWW-2021

공식 코드

Dual Side Deep Context-aware Modulation for Social Recommendation

https://github.com/EnyanDai/NRGNN

공식 코드

NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

https://github.com/FFrankyy/DrBC

공식 코드

Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach

https://github.com/Fang6ang/KBGNN

공식 코드

Kernel-based Substructure Exploration for Next POI Recommendation

https://github.com/FedML-AI/FedGraphNN

공식 코드

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

https://github.com/Feiyu-Yao/Full-Body-Motion-Reconstruction-with-Sparse-Sensing-from-Graph-Perspective

공식 코드

Full-Body Motion Reconstruction with Sparse Sensing from Graph Perspective

https://github.com/FerranAlet/modular-metalearning

공식 코드

Neural Relational Inference with Fast Modular Meta-learning

https://github.com/FilippoMB/Benchmark_dataset_for_graph_classification

공식 코드

Spectral Clustering with Graph Neural Networks for Graph Pooling

https://github.com/FilippoMB/Pyramidal-Reservoir-Graph-Nerual-Networks

공식 코드

Pyramidal Reservoir Graph Neural Network

https://github.com/FilippoMB/Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling

공식 코드

Spectral Clustering with Graph Neural Networks for Graph Pooling

https://github.com/Frank-Wang-oss/FCSTGNN

공식 코드

Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data

https://github.com/Friger/GAGNN

공식 코드

Group-Aware Graph Neural Network for Nationwide City Air Quality Forecasting

https://github.com/Friger/HighAir

공식 코드

HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method

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