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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/ivam-he/BernNet

공식 코드

BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation

https://github.com/ivanniu/inversiongnn

공식 코드

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization

https://github.com/j-f-cheng/g-fars-3dpartgrouping

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G-FARS: Gradient-Field-based Auto-Regressive Sampling for 3D Part Grouping

https://github.com/jacklinkk/torchgrl

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Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments

https://github.com/jadecurl/predicting-viral-rumors-and-vulnerable-users

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Predicting Viral Rumors and Vulnerable Users for Infodemic Surveillance

https://github.com/jahirsadik/cohet-implementation

공식 코드

Enhancing Heterogeneous Multi-Agent Cooperation in Decentralized MARL via GNN-driven Intrinsic Rewards

https://github.com/jakub-zarzycki2022/gattaca

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Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks: The GATTACA Framework

https://github.com/jamesyifan/DisenHAN

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DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation

https://github.com/jarrycyx/unn

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CUTS: Neural Causal Discovery from Irregular Time-Series Data

https://github.com/jasonzy121/TextGNN

공식 코드

TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search

https://github.com/jbcdnr/gretel-path-extrapolation

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Extrapolating paths with graph neural networks

https://github.com/jcastro295/gegengnn

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Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction

https://github.com/jcy132/PatchGCL

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Patch-wise Graph Contrastive Learning for Image Translation

https://github.com/jeff-sue/urt

공식 코드

Unsupervised Mutual Learning of Dialogue Discourse Parsing and Topic Segmentation

https://github.com/jeongwhanchoi/panda

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PANDA: Expanded Width-Aware Message Passing Beyond Rewiring

https://github.com/jiafan-ucas/hgnn-ima

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Representation Learning with Mutual Influence of Modalities for Node Classification in Multi-Modal Heterogeneous Networks

https://github.com/jiahaoLjh/HumanDepth

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HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization

https://github.com/jiahaoLjh/PoseGrouping

공식 코드

Learning Spatial Context with Graph Neural Network for Multi-Person Pose Grouping

https://github.com/jianhao2016/GPRGNN

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Adaptive Universal Generalized PageRank Graph Neural Network

https://github.com/jiaqima/CopulaGNN

공식 코드

CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks

https://github.com/jiaqingxie/deepprotein

공식 코드

DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning

https://github.com/jiaweihe1996/GMTracker

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Learnable Graph Matching: A Practical Paradigm for Data Association

https://github.com/jiaweixue/multiwavecovidprediction

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Multiwave COVID-19 Prediction from Social Awareness using Web Search and Mobility Data

https://github.com/jiaxililearn/hrgcn

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HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks

https://github.com/jiayuzhai1207/bregmangnn

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Bregman Graph Neural Network

https://github.com/jiazheng-xing/gghm

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Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching

https://github.com/jindongli-ai/cvtgad

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CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection

https://github.com/jingqiangchen/kbsumm

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An entity-guided text summarization framework with relational heterogeneous graph neural network

https://github.com/jiwoncpark/node-to-joy

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Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

https://github.com/jiyawang/ppgnn

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Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learning

https://github.com/jjzhou012/I2BGNN

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Identity Inference on Blockchain using Graph Neural Network

https://github.com/jla-gardner/nnp-pre-training

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Synthetic pre-training for neural-network interatomic potentials

https://github.com/jliu/graph-normalizing-flows

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Graph Normalizing Flows

https://github.com/joeloskarsson/tgnn4i

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Temporal Graph Neural Networks for Irregular Data

https://github.com/joepstorm/microscale-gnn-surrogate

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A Microstructure-based Graph Neural Network for Accelerating Multiscale Simulations

https://github.com/johncai117/DAMSL

공식 코드

DAMSL: Domain Agnostic Meta Score-based Learning

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