1 citations · 1 across the 1 of their papers we have counts for
2 papers
stat.ML2021★ 1 cited
Is the Number of Trainable Parameters All That Actually Matters?
Amélie Chatelain, Amine Djeghri, Daniel Hesslow +2
Recent work has identified simple empirical scaling laws for language models, linking compute budget, dataset size, model size, and autoregressive modeling loss. The validity of th…
hep-ph2019
Neutrino decoherence in presence of strong gravitational fields
Amélie Chatelain, Maria Cristina Volpe
We explore the impact of strong gravitational fields on neutrino decoherence. To this aim, we employ the density matrix formalism to describe the propagation of neutrino wave packe…