1 citations · 1 across the 6 of their papers we have counts for
7 papers
ASTROLABE: A 3D Particle-Level Surrogate for Cosmology Simulation with Physical Flow Matching
Ibrahim Elsharkawy, David Curtin, Yonatan Kahn +1
The microphysics of dark matter (DM) is imprinted on cosmological structure across an enormous dynamic range. Nonlinear cosmological observables are most reliably modeled with N-bo…
Statistical Properties of Training & Generalization
Itay Lavie, Noam Levi, Yonatan Kahn
Deep learning has managed to evade numerous intuitions from classical statistics to achieve unprecedented performance on a number of real-world tasks. In this article, we investiga…
Generative models on phase space
Zachary Bogorad, Ibrahim Elsharkawy, Yonatan Kahn +2
Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are partic…
Quantum Calculations of the Cavity Shift in Electron Magnetic Moment Measurements
Hannah Day, Roni Harnik, Yonatan Kahn +2
The measurement of the anomalous electron magnetic moment through quantum transitions of a single trapped electron is the most stringent test of quantum field theory. These e…
Contrastive Normalizing Flows for Uncertainty-Aware Parameter Estimation
Ibrahim Elsharkawy, Yonatan Kahn
Estimating physical parameters from data is a crucial application of machine learning (ML) in the physical sciences. However, systematic uncertainties, such as detector miscalibrat…
Scaling Laws in Jet Classification
Joshua Batson, Yonatan Kahn
We demonstrate the emergence of scaling laws in the benchmark top versus QCD jet classification problem in collider physics. Six distinct physically-motivated classifiers exhibit p…
Feature Learning and Generalization in Deep Networks with Orthogonal Weights
Hannah Day, Yonatan Kahn, Daniel A. Roberts
Fully-connected deep neural networks with weights initialized from independent Gaussian distributions can be tuned to criticality, which prevents the exponential growth or decay of…