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Graph Representation Learning

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The goal of Graph Representation Learning is to construct a set of features (‘embeddings’) representing the structure of the graph and the data thereon. We can distinguish among Node-wise embeddings, representing each node of the graph, Edge-wise embeddings, representing each edge in the graph, and Graph-wise embeddings representing the graph as a whole.

Source: SIGN: Scalable Inception Graph Neural Networks

코드

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

https://github.com/holipori/mimic-diff-vqa

공식 코드

Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering

https://github.com/honggen-zhang/hasa-ckge

공식 코드

HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding

https://github.com/hopkin-ghp/QuatDE

공식 코드

QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion

https://github.com/hping666/HSDAG

공식 코드

A Structure-Aware Framework for Learning Device Placements on Computation Graphs

https://github.com/huda-hakami/learning-to-borrow-for-kgs

공식 코드

Learning to Borrow -- Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion

https://github.com/hwwang55/GraphGAN

공식 코드

GraphGAN: Graph Representation Learning with Generative Adversarial Nets

https://github.com/hwwang55/MKR

공식 코드

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

https://github.com/hysonlab/biomedkg

공식 코드

Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs

https://github.com/hyzhang98/epagcl

공식 코드

Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?

https://github.com/ibm/otter-knowledge

공식 코드

Otter-Knowledge: benchmarks of multimodal knowledge graph representation learning from different sources for drug discovery

https://github.com/icm1018/geaet

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Graph External Attention Enhanced Transformer

https://github.com/ifding/uhgr

공식 코드

Unsupervised Hierarchical Graph Representation Learning by Mutual Information Maximization

https://github.com/iieir-km/ComplEx-NNE_AER

공식 코드

Improving Knowledge Graph Embedding Using Simple Constraints

https://github.com/iieir-km/RUGE

공식 코드

Knowledge Graph Embedding with Iterative Guidance from Soft Rules

https://github.com/intellabs/gravi-t

공식 코드

VideoSAGE: Video Summarization with Graph Representation Learning

https://github.com/iodike/chronokge

공식 코드

Temporal Knowledge Graph Reasoning with Low-rank and Model-agnostic Representations

https://github.com/isi-usc-edu/gttf

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Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning

https://github.com/j-adamczyk/ltp

공식 코드

Strengthening structural baselines for graph classification using Local Topological Profile

https://github.com/jasperzhong/GNNFlow

공식 코드

GNNFlow: A Distributed Framework for Continuous Temporal GNN Learning on Dynamic Graphs

https://github.com/jayachaturvedi/pain_in_mental_health

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Development of a Knowledge Graph Embeddings Model for Pain

https://github.com/jayroxis/dam-pytorch

공식 코드

Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)

https://github.com/jcyk/gtos

공식 코드

Graph Transformer for Graph-to-Sequence Learning

https://github.com/jhljx/CTGCN

공식 코드

K-Core based Temporal Graph Convolutional Network for Dynamic Graphs

https://github.com/jinlin2021/curegraph

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CureGraph: Contrastive Multi-Modal Graph Representation Learning for Urban Living Circle Health Profiling and Prediction

https://github.com/jjzhou012/GDAug-Survey

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Data Augmentation on Graphs: A Technical Survey

https://github.com/joaopedromattos/gnee

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Semi-Supervised Graph Attention Networks for Event Representation Learning

https://github.com/jordan7186/page

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PAGE: Prototype-Based Model-Level Explanations for Graph Neural Networks

https://github.com/junhua/stged

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Spatial-Temporal Graph Representation Learning for Tactical Networks Future State Prediction

https://github.com/junkangwu/DisenKGAT

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DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network

https://github.com/junxia97/awesome-pre-training-on-graphs

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A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications

https://github.com/junxia97/simgrace

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SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation

https://github.com/jwzhanggy/DifNet

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Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised Classification

https://github.com/jwzhanggy/isocapsnet

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Iso-CapsNet: Isomorphic Capsule Network for Brain Graph Representation Learning

https://github.com/jyf123/html

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Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning

https://github.com/k-melnyk/deep-metastability

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Understanding microbiome dynamics via interpretable graph representation learning

https://github.com/kaike-zhang/dyted

공식 코드

DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph

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