Graph Neural Networks Embedding Tools

There are 14 graph neural networks tools tracked. 2 score above 50 (established tier). The highest-rated is Accenture/AmpliGraph at 56/100 with 2,228 stars.

Get all 14 projects as JSON

curl "https://pt-edge.onrender.com/api/v1/datasets/quality?domain=embeddings&subcategory=graph-neural-networks&limit=20"

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#	Tool	Score	Tier	Stars	Language
1	Accenture/AmpliGraph Python library for Representation Learning on Knowledge Graphs...	56	Established	2,228	Python
2	benedekrozemberczki/graph2vec A parallel implementation of "graph2vec: Learning Distributed...	50	Established	933	Python
3	DeepGraphLearning/graphvite GraphVite: A General and High-performance Graph Embedding System	47	Emerging	1,270	C++
4	bi-graph/Emgraph A Python library for knowledge graph representation learning (graph embedding).	40	Emerging	39	Python
5	nju-websoft/muKG μKG: A Library for Multi-source Knowledge Graph Embeddings and Applications,...	39	Emerging	112	Python
6	llm-db/MLKV MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based...	34	Emerging	8	—
7	soda-inria/ken_embeddings KEN: Relational Data Embeddings	31	Emerging	34	Python
8	XiaShan1227/Graphormer Do Transformers Really Perform Bad for Graph Representation? [NIPS-2021]	31	Emerging	61	Python
9	zjunlp/KNN-KG [NLPCC 2023] Reasoning Through Memorization: Nearest Neighbor Knowledge...	31	Emerging	55	Python
10	cnclabs/ICE ICE: Item Concept Embedding	28	Experimental	89	C++
11	tapadeep/PBGENA Parallelized Binary embedding GENerator for Attributed graphs	22	Experimental	15	Python
12	GregorLueg/genewalkR node2vec-based CompBio methods in R	21	Experimental	—	R
13	kshitijbhandari/Unsupervised-Clustering-of-Actor-Movie-Bipartite-Graphs-Using-Random-Walk-Embeddings Grouped 3,411 actors into 3 communities and 1,292 movies into 50 clusters...	14	Experimental	—	Jupyter Notebook
14	AndreasLF/HowLowCanYouGo 🚀 HowLowCanYouGo – Official implementation of "How Low Can You Go? Searching...	14	Experimental	6	Python

Comparisons in this category

AmpliGraph and Emgraph (56 vs 40)