LLM embeddings condition generative networks for LHC events, yielding faster convergence, higher quality, and generalization to unseen processes.
Inferring astrophysics and dark matter properties from 21 cm tomography using deep learning
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
years
2026 4roles
background 2representative citing papers
A review chapter on tools for inferring galaxy and IGM properties from the 21 cm signal using the initial SKA-Low array configuration.
An overview summarizing SKA-Low 21cm experiments for power spectrum, tomography, 21-cm forest, and cross-correlations, plus critical telescope features, building on the 2015 SKA Science Book.