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

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 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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