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/nellaker-group/placenta

공식 코드

A New Graph Node Classification Benchmark: Learning Structure from Histology Cell Graphs

https://github.com/neuir/co-gat

공식 코드

Multi-Evidence based Fact Verification via A Confidential Graph Neural Network

https://github.com/ngminhtri0394/GEFA

공식 코드

GEFA: Early Fusion Approach in Drug-Target Affinity Prediction

https://github.com/nikita6187/transportplanningdataset

공식 코드

Graph neural network surrogate for strategic transport planning

https://github.com/nikolaimerkel/reordering

공식 코드

Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study

https://github.com/ninggirsu/run-gnn

공식 코드

Towards Enhancing Relational Rules for Knowledge Graph Link Prediction

https://github.com/niuzehao/gnn-gp

공식 코드

Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning

https://github.com/nju-websoft/HyperKA

공식 코드

Knowledge Association with Hyperbolic Knowledge Graph Embeddings

https://github.com/nju-websoft/tkgc

공식 코드

Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data

https://github.com/njuhtc/LEDG

공식 코드

Learning to Evolve on Dynamic Graphs

https://github.com/nkkchem/pf-gnn_pli

공식 코드

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks

https://github.com/nklskrmnn/hiegnet

공식 코드

HIEGNet: A Heterogenous Graph Neural Network Including the Immune Environment in Glomeruli Classification

https://github.com/nnzhan/Graph-WaveNet

공식 코드

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

https://github.com/nnzhan/MTGNN

공식 코드

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

https://github.com/nnzhan/traversenet

공식 코드

TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting

https://github.com/nobrowning/seq_hgnn

공식 코드

Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph

https://github.com/nokpil/rain

공식 코드

Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network

https://github.com/non-void/localmocap

공식 코드

A Locality-based Neural Solver for Optical Motion Capture

https://github.com/nsidn98/informarl

공식 코드

Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation

https://github.com/ntkien1904/DegFairGNN

공식 코드

On Generalized Degree Fairness in Graph Neural Networks

https://github.com/ntuhep-qml/qcgnn

공식 코드

Jet Discrimination with Quantum Complete Graph Neural Network

https://github.com/nust-machine-intelligence-laboratory/hgpu

공식 코드

Hierarchical Graph Pattern Understanding for Zero-Shot VOS

https://github.com/nutcrtnk/dhgnet

공식 코드

Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph

https://github.com/nvlabs/gnn-decoder

공식 코드

Graph Neural Networks for Channel Decoding

https://github.com/nyu-dl/dl4chem-geometry

공식 코드

Molecular geometry prediction using a deep generative graph neural network

https://github.com/nyushcs/moleculargpt

공식 코드

MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

https://github.com/ocram17/engagementgnn

공식 코드

Predicting Tweet Engagement with Graph Neural Networks

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

공식 코드

Multi-task Learning for Sparse Traffic Forecasting

https://github.com/odor-pair/odor-pair

공식 코드

Olfactory Label Prediction on Aroma-Chemical Pairs

https://github.com/oj9040/GraphSAGE_RL

공식 코드

Advancing GraphSAGE with A Data-Driven Node Sampling

https://github.com/omicsml/dance

공식 코드

Graph Neural Networks for Multimodal Single-Cell Data Integration

https://github.com/opendrivelab/toponet

공식 코드

Graph-based Topology Reasoning for Driving Scenes

https://github.com/openperceptionx/hdgt

공식 코드

HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encoding

https://github.com/outfit-net/outfit-commpatibility

공식 코드

Fashion Recommendation: Outfit Compatibility using GNN

https://github.com/oval-group/GNN_branching

공식 코드

Neural Network Branching for Neural Network Verification

https://github.com/papercodeeric/lfh

공식 코드

Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs

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