This process is detailed in our recent publication, QirK: Question Answering via Intermediate Representation on Knowledge Graphs ... high-value machine learning and AI solutions across various ...

The aim of the workshop is to connect researchers working on this topic and surface novel research ideas and collaboration ...

The interplay between graph analytics and large language models (LLMs) represents a promising frontier for advancing ...

The course requires basic knowledge of linear algebra ... classification and clustering is beneficial. Graphs are among the most widely-used data structures in machine learning. Their power comes from ...

Paper: Accelerating scientific discovery with generative knowledge extraction, graph-based representation ... published in the journal Machine Learning explored the integration of generative ...

More information: Xiaorui Su et al, Interpretable identification of cancer genes across biological networks via transformer-powered graph representation learning, Nature Biomedical Engineering (2025).

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