#Graph Neural Networks

3 posts tagged with "Graph Neural Networks"

The Historical Accident That Split Drug Design in Two (And the Contrastive Model That Reunites It)

2026-01-30T16:00:00Z•12 min read

#drug discovery #contrastive learning #computational biology #virtual screening #protein-ligand interactions #graph neural networks #machine learning

Structure-based and ligand-based drug design evolved as separate fields solving the same problem. ConGLUDe, a contrastive geometric learning model, unifies both approaches and outperforms specialist methods on realistic benchmarks without requiring pre-defined binding pockets.

When the Algorithm Can't Explain Itself: ML Interpretability in Precision Oncology

2026-01-03T10:00:00Z•19 min read

#machine learning #precision oncology #explainability #genomics #graph neural networks #clinical ai

Machine learning models now outperform FDA-approved biomarkers in predicting treatment response, but the best-performing models often resist explanation. Here's how precision oncology is navigating the trade-off between performance and interpretability.

Beyond the Page: The Rise of Graph-Structured Knowledge in Language Models

2024-10-15T13:36:43+01:00•34 min read

#ai #machine learning #nlp #knowledge graphs #graph neural networks

How graph-based representations are transforming language models beyond sequential text to unlock deeper reasoning capabilities