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/wangyu0627/gc-hgnn

공식 코드

Generative-Contrastive Heterogeneous Graph Neural Network

https://github.com/wayfear/brainnetworktransformer

공식 코드

MHNet: Multi-view High-order Network for Diagnosing Neurodevelopmental Disorders Using Resting-state fMRI

https://github.com/wayfear/fbnetgen

공식 코드

FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation

https://github.com/wdimmy/graphretrieval

공식 코드

An Empirical Study of Retrieval-enhanced Graph Neural Networks

https://github.com/wenbin-lin/OcclusionFusion

공식 코드

OcclusionFusion: Occlusion-aware Motion Estimation for Real-time Dynamic 3D Reconstruction

https://github.com/wendongbi/KT-GNN

공식 코드

Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network

https://github.com/wendongbi/MMGNN

공식 코드

MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution

https://github.com/wendongbi/th-gnn

공식 코드

Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks

https://github.com/wenqi006/slidegraph

공식 코드

SlideGraph+: Whole Slide Image Level Graphs to Predict HER2Status in Breast Cancer

https://github.com/wenqifan03/GraphRec-WWW19

공식 코드

Graph Neural Networks for Social Recommendation

https://github.com/wentao-xu/shgnn

공식 코드

SHGNN: Structure-Aware Heterogeneous Graph Neural Network

https://github.com/wenweigu/isolate

공식 코드

Identifying Performance Issues in Cloud Service Systems Based on Relational-Temporal Features

https://github.com/westny/mtp-go

공식 코드

Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory Prediction

https://github.com/whuminghui/neunet

공식 코드

Joint Learning Neuronal Skeleton and Brain Circuit Topology with Permutation Invariant Encoders for Neuron Classification

https://github.com/williamweiwu/williamweiwu.github.io

공식 코드

Hashing-Accelerated Graph Neural Networks for Link Prediction

https://github.com/wondercs1213/uniea

공식 코드

Unifying Dual-Space Embedding for Entity Alignment via Contrastive Learning

https://github.com/woodcutter1998/gdgnn

공식 코드

Geodesic Graph Neural Network for Efficient Graph Representation Learning

https://github.com/wouterwln/neuralfactortrees

공식 코드

Node Classification in Random Trees

https://github.com/wurenzhi/hyper_label_model

공식 코드

Learning Hyper Label Model for Programmatic Weak Supervision

https://github.com/wusw14/gnn-in-rs

공식 코드

Graph Neural Networks in Recommender Systems: A Survey

https://github.com/wuyxin/falcon-glfrontiers

공식 코드

Efficient Automatic Machine Learning via Design Graphs

https://github.com/wuyxin/graphmetro

공식 코드

GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts

https://github.com/wwbrannon/congrat

공식 코드

ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddings

https://github.com/xhcdream/kcgn

공식 코드

Knowledge-aware Coupled Graph Neural Network for Social Recommendation

https://github.com/xhcdream/sr-hgnn

공식 코드

Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks

https://github.com/xhuang2016/gnn-benchmark

공식 코드

Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass

https://github.com/xiangwang1223/knowledge_graph_attention_network

공식 코드

KGAT: Knowledge Graph Attention Network for Recommendation

https://github.com/xiangyan93/molecules-enumerate

공식 코드

Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation

https://github.com/xiannanhuang/mpstn

공식 코드

Leveraging Intra-Period and Inter-Period Features for Enhanced Passenger Flow Prediction of Subway Stations

https://github.com/xianyuco/ss-gnn

공식 코드

SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction

https://github.com/xiaofangxd/KEGNAS

공식 코드

Knowledge-aware Evolutionary Graph Neural Architecture Search

https://github.com/xiaolin-cs/bemap

공식 코드

BeMap: Balanced Message Passing for Fair Graph Neural Network

https://github.com/xiaoxinhe/tape_arxiv_2023

공식 코드

Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

https://github.com/xiefeng69/epignn

공식 코드

EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting

https://github.com/xinlihao/aero

공식 코드

From Chaos to Clarity: Time Series Anomaly Detection in Astronomical Observations

https://github.com/xinshuoweng/GNN3DMOT

공식 코드

GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning

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