A Python client for the Neo4j Graph Data Science (GDS) library
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Updated
Oct 4, 2024 - Python
A Python client for the Neo4j Graph Data Science (GDS) library
A new benchmark of meaningful tabular datasets with known graph structure
The integration of HugeGraph with artificial intelligence
Solutions to homework problems and programming assignments for Stanford's cs224w Machine Learning with Graphs (2021) course.
Code repository for the ECCV paper "MSD: A Benchmark Dataset for Floor Plan of Building Complexes".
Project page for the ECCV 2024 paper "MSD: A Benchmark Dataset for Floor Plan Generation of Building Complexes". ArXiv pre-print: https://arxiv.org/abs/2407.10121.
Applications using Parallel Graph AnalytiX (PGX) from Oracle Labs
Machine learning on graphs
ComptoxAI - An artificial Intelligence toolkit for computational toxicology
OpenABC-D is a large-scale labeled dataset generated by synthesizing open source hardware IPs. This dataset can be used for various graph level prediction problems in chip design.
Official implementation of the InfFus 2024 paper "Identifying the Hierarchical Emotional Areas in the Human Brain Through Information Fusion"
A benchmark suite for Graph Machine Learning
Detection of rare child diseases by applying graph machine learning to a remote dataset with federated machine learning
Graph machine learning architectures for learning temporal and spatial patterns of brain activation from fMRI images. Two downstream tasks are implemented: (1) brain activation prediction duration language tasks (link prediction) and (2) performance prediction from neural patterns (graph regression)
📖 A review of KGEM packages and frameworks at https://pykeen.github.io/kgem-software-review.
[ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改善类别不平衡节点分类
Given an input graph (ArangoDB or PyG) it generates graph embeddings using Low-Code framework built on top of PyG.
Precision Medicine Knowledge Graph (PrimeKG)
GraphXAI: Resource to support the development and evaluation of GNN explainers
ALMOST: Adversarial Learning to Mitigate Oracle-less ML Logic Locking Attacks via Synthesis Tuning
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