Knowledge Graphs
Showing 12 of 12 projects
A unified, comprehensive, and efficient Python/PyTorch library for reproducing and developing recommendation algorithms.
A distributed system for learning graph embeddings from large-scale graphs with billions of entities and trillions of edges.
A Python library for machine learning on graphs and networks, offering state-of-the-art algorithms for tasks like node classification and link prediction.
A curated list of network embedding techniques, including papers, implementations, and related resources for graph representation learning.
A curated collection of research papers and software for explainable graph machine learning and reasoning.
A curated collection of must-read academic papers on knowledge representation learning and knowledge embedding, with an associated open-source toolkit.
Cleora is a fast, deterministic graph embedding engine that computes all random walks in a single matrix multiplication, requiring no GPUs or negative sampling.
An AI system that incrementally generates scientific paper drafts by predicting links between concepts and generating text sections.
An enterprise-grade Graph RAG framework combining hierarchical tree navigation with knowledge graph reasoning for verifiable, on-premise AI.
A resource and evaluation framework for benchmarking link prediction models on large-scale, heterogeneous biomedical knowledge graphs.
A neural network system that generates English Wikipedia-style biographies from Semantic Web triples using encoder-decoder models.
Graph embedding framework implementing TransE, TransH, TransR, TransD, and TransSparse models for knowledge graph representation learning.
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