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Graph Neural Network

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

https://github.com/zjunet/G-Tuning

공식 코드

Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns

https://github.com/zjunet/graphadapter

공식 코드

Can GNN be Good Adapter for LLMs?

https://github.com/zknus/iclr2024-frond

공식 코드

Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND

https://github.com/zknus/neurips-2024-dragon

공식 코드

Distributed-Order Fractional Graph Operating Network

https://github.com/zknus/torchfde

공식 코드

Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND

https://github.com/zkxinxin/hcmgnn

공식 코드

Heterogeneous Causal Metapath Graph Neural Network for Gene-Microbe-Disease Association Prediction

https://github.com/zkz-brain/ci-gnn

공식 코드

CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis

https://github.com/zlinaf/powergear

공식 코드

PowerGear: Early-Stage Power Estimation in FPGA HLS via Heterogeneous Edge-Centric GNNs

https://github.com/zohairshafi/Graph-SCP

공식 코드

Graph-SCP: Accelerating Set Cover Problems with Graph Neural Networks

https://github.com/zongyi-li/graph-pde

공식 코드

Multipole Graph Neural Operator for Parametric Partial Differential Equations

https://github.com/zorzi-s/polyworldpretrainednetwork

공식 코드

PolyWorld: Polygonal Building Extraction with Graph Neural Networks in Satellite Images

https://github.com/zrgcityu/pegfan

공식 코드

Permutation Equivariant Graph Framelets for Heterophilous Graph Learning

https://github.com/zwangeo/autogel

공식 코드

AutoGEL: An Automated Graph Neural Network with Explicit Link Information

https://github.com/zyl199710/hipgnn

공식 코드

Rethinking Cancer Gene Identification through Graph Anomaly Analysis

https://github.com/zylMozart/HiGNN

공식 코드

Learn from Heterophily: Heterophilous Information-enhanced Graph Neural Network

https://github.com/zyli93/saecon

공식 코드

Powering Comparative Classification with Sentiment Analysis via Domain Adaptive Knowledge Transfer

https://github.com/zzhang1987/Factor-Graph-Neural-Network

공식 코드

Factor Graph Neural Network

https://github.com/zzy979/gnn-recommendation

공식 코드

RHCO: A Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning for Large-scale Graphs

https://gitlab.cern.ch/gdl4hep/hls4ml-etx4velo

공식 코드

Comparative Analysis of FPGA and GPU Performance for Machine Learning-Based Track Reconstruction at LHCb

https://gitlab.com/europeanspaceagency/pylattice2d

공식 코드

Differentiable graph-structured models for inverse design of lattice materials

https://gitlab.com/fdlm/olga

공식 코드

Artist Similarity with Graph Neural Networks

https://gitlab.com/hanfengzhai2/gnn-fem-polyplas

공식 코드

Stress Predictions in Polycrystal Plasticity using Graph Neural Networks with Subgraph Training

https://gitlab.com/micronano_public/tb-mlff

공식 코드

Evaluating the Transferability of Machine-Learned Force Fields for Material Property Modeling

https://worksheets.codalab.org/worksheets/0x01838644724a433c932bef4cb5c42fbd

공식 코드

Graph-based, Self-Supervised Program Repair from Diagnostic Feedback

https://github.com/0h-n0/tfdbonas

Deep Neural Architecture Search with Deep Graph Bayesian Optimization

https://github.com/0h-n0/thdbonas

Deep Neural Architecture Search with Deep Graph Bayesian Optimization

https://github.com/2023-MindSpore-4/Code12/tree/main/dengzhaohong/GFS_MindSpore-main

Graph Fuzzy System: Concepts, Models and Algorithms

https://github.com/2023-MindSpore-4/Code16/tree/main/baopeng/HW-GTGCN

Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

https://github.com/ADL-TBB/tbb-bridge-dpi

BridgeDPI: A Novel Graph Neural Network for Predicting Drug-Protein Interactions

https://github.com/AICPS/roadscene2vec

Spatio-Temporal Scene-Graph Embedding for Autonomous Vehicle Collision Prediction

https://github.com/Aditya239233/GNNExplainer

GNNExplainer: Generating Explanations for Graph Neural Networks

https://github.com/Ahren09/dygetviz

Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks

https://github.com/AidanRocke/vertex_prediction

Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++

https://github.com/AlexDuvalinho/GNNE_eval

GNNExplainer: Generating Explanations for Graph Neural Networks

https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need

Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction

https://github.com/AstraZeneca/chemicalx

MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions

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