391 citations · 2.1k across the 34 of their papers we have counts for
4 papers · 1 filter
Identifying charged particle background events in X-ray imaging detectors with novel machine learning algorithms
D. R. Wilkins, S. W. Allen, E. D. Miller +8
Space-based X-ray detectors are subject to significant fluxes of charged particles in orbit, notably energetic cosmic ray protons, contributing a significant background. We develop…
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel
Stanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul +3
In suitably initialized wide networks, small learning rates transform deep neural networks (DNNs) into neural tangent kernel (NTK) machines, whose training dynamics is well-approxi…
Training independent subnetworks for robust prediction
Marton Havasi, Rodolphe Jenatton, Stanislav Fort +5
Recent approaches to efficiently ensemble neural networks have shown that strong robustness and uncertainty performance can be achieved with a negligible gain in parameters over th…
The Break-Even Point on Optimization Trajectories of Deep Neural Networks
Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort +4
The early phase of training of deep neural networks is critical for their final performance. In this work, we study how the hyperparameters of stochastic gradient descent (SGD) use…