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A collection of Graph Embedding methods in Python
A collection of Graph Embedding methods in Python
A collection of Graph Embedding methods in Python. 🧠💎 This repository provides hands-on implementations of essential graph embedding algorithms like: ▪️…
A collection of Graph Embedding methods in Python
·linkedin.com·
A collection of Graph Embedding methods in Python
GitHub - a-s-g93/neo4j-runway: End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
GitHub - a-s-g93/neo4j-runway: End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages. - a-s-g93/neo4j-runway
·github.com·
GitHub - a-s-g93/neo4j-runway: End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
MLX-graphs — mlx-graphs 0.0.3 documentation
MLX-graphs — mlx-graphs 0.0.3 documentation
Apple presented MLX-graphs: the GNN library for the MLX framework specifically optimized for Apple Silicon. Since the CPU/GPU memory is shared on M1/M2/M3, you don’t have to worry about moving tensors around and at the same time you can enjoy massive GPU memory of latest M2/M3 chips (64 GB MBPs and MacMinis are still much cheaper than A100 80 GB). For starters, MLX-graphs includes GCN, GAT, GIN, GraphSAGE, and MPNN models and a few standard datasets.
·mlx-graphs.github.io·
MLX-graphs — mlx-graphs 0.0.3 documentation