Papers with Code 아카이브

Graph Neural Network

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

https://github.com/ml-jku/vnegnn

EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction

https://github.com/ml4bio/rna-fm

gRNAde: Geometric Deep Learning for 3D RNA inverse design

https://github.com/mtiezzi/lpgnn

A Lagrangian Approach to Information Propagation in Graph Neural Networks

https://github.com/muhanzhang/NestedGNN

Nested Graph Neural Networks

https://github.com/mwcvitkovic/open-vocabulary-learning-on-source-code-with-a-graph-structured-cache--code-preprocessor

Open Vocabulary Learning on Source Code with a Graph-Structured Cache

https://github.com/nealgravindra/self-supervsed_edge_feats

Self-supervised edge features for improved Graph Neural Network training

https://github.com/negotiatorvivian/PDP-SP

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

https://github.com/negotiatorvivian/SAT-Solver

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

https://github.com/neural-operator/graph-pde

Multipole Graph Neural Operator for Parametric Partial Differential Equations

https://github.com/neuraloperator/graph-pde

Multipole Graph Neural Operator for Parametric Partial Differential Equations

https://github.com/nianticlabs/relpose-gnn

Visual Camera Re-Localization Using Graph Neural Networks and Relative Pose Supervision

https://github.com/nmvdlei/PPMI_MAGNN

MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding

https://github.com/nodarsensor/medium-keypoint-autocal

SuperGlue: Learning Feature Matching with Graph Neural Networks

https://github.com/nslab-cuk/halal-or-not

Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

https://github.com/ognjenkundacina/graph-neural-network-state-estimation

State Estimation in Electric Power Systems Leveraging Graph Neural Networks

https://github.com/omri1348/LRGA

Global Attention Improves Graph Networks Generalization

https://github.com/omri1348/LRGA/tree/master/ogb/examples/linkproppred

Global Attention Improves Graph Networks Generalization

https://github.com/omron-sinicx/weavenet

WeaveNet for Approximating Two-sided Matching Problems

https://github.com/ondrejba/action_attention_iclr_22

Contrastive Learning of Structured World Models

https://github.com/open-catalyst-project/adsorbml

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

https://github.com/opendrivelab/hdgt

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

https://github.com/panwangwin/SpatialTemporalNetTrainer-pytorch

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

https://github.com/peizeli96/Object-attribute-matters-in-visual-question-answering

Object Attribute Matters in Visual Question Answering

https://github.com/peizhaoli05/EDA_GNN

Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking

https://github.com/pnnl/expert2

Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph Transformers

https://github.com/pollyjuice74/5g-decoder

Graph Neural Networks for Channel Decoding

https://github.com/prachiisc/SHARC

Supervised Hierarchical Clustering using Graph Neural Networks for Speaker Diarization

https://github.com/proroklab/gnn_pathplanning

Graph Neural Networks for Decentralized Multi-Robot Path Planning

https://github.com/pulkit1joshi/SimGNN

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation

https://github.com/pwc-1/Paper-9/tree/main/6/Cybertron

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

https://github.com/pwc-1/Paper-9/tree/main/7/RGNN

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

https://github.com/pygod-team/pygod

One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks

https://github.com/q3erf/GLAM

Joint Graph Learning and Matching for Semantic Feature Correspondence

https://github.com/qiaoyu-tan/s2gae

MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs

https://github.com/rafa-cxg/PySGG-cxg

Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation

https://github.com/razvanc92/enhancenet

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

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