20 citations · 28 across the 12 of their papers we have counts for
3 papers · 1 filter
Do Quantum Models Scale Like LLMs?
David S. Berman, Ying-Jer Kao, Roger G. Melko +1
In this work, we study the neural scaling laws of RydbergGPT, an autoregressive transformer model trained on qubit projective measurement data gathered from interacting Rydberg ato…
A Machine Learning Approach to the Nirenberg Problem
Gianfranco Cortés, Maria Esteban-Casadevall, Yueqing Feng +4
This work introduces the Nirenberg Neural Network: a numerical approach to the Nirenberg problem of prescribing Gaussian curvature on for metrics that are pointwise conformal…
Grokking vs. Learning: Same Features, Different Encodings
Dmitry Manning-Coe, Jacopo Gliozzi, Alexander G. Stapleton +4
Grokking typically achieves similar loss to ordinary, "steady", learning. We ask whether these different learning paths - grokking versus ordinary training - lead to fundamental di…