This page shows the most relevant public items for Graph Neural Networks, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Paper • Nov 29, 2023 • Nature • Amil Merchant, Simon Batzner, Samuel S. Schoenholz, Muratahan Aykol, Gowoon Cheon, Ekin Dogus Cubuk
The discovery of novel functional materials is essential for technological progress in batteries, solar cells, and computation, but traditionally relies on expensive, trial-and-error experimentatio...
Paper • Nov 14, 2023 • Science • Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Alexander Alet, Suman Ravuri, Timo Ewalds, Zachary Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Jacklynn Stott, Oriol Vinyals, Shakir Mohamed, Peter Battaglia
Global medium-range weather forecasting has long been dominated by massive, compute-intensive numerical weather prediction (NWP) models governed by atmospheric physics equations. We present GraphCa...
Paper • Feb 23, 2026 • bioRxiv • Zhang, X., Jeong, E., Yan, C., Feng, Y.
Predicting novel drug indications requires synthesizing vast, heterogeneous networks of gene, disease, and chemical data. We upgrade the CellAwareGNN foundation model into a multi-agent swarm archi...
Paper • Feb 20, 2026 • bioRxiv • Ishaan Batta, Meenu Ajith, Vince Calhoun
Uncovering the network mechanisms of cognitive assessments requires generative frameworks that model brain connectivity in conjunction with demographic variables. We present a conditional graph var...
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Use weekly for fast-moving updates, monthly for stable trend confirmation, and all-time for evergreen references. This guidance is specific to Graph Neural Networks topic page on Attendemia and is written so it still makes sense without reading other sections on the page.
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