4 citations · 4 across the 3 of their papers we have counts for
5 papers
Random Label Prediction Heads for Studying Memorization in Deep Neural Networks
Marlon Becker, Jonas Konrad, Luis Garcia Rodriguez +1
We introduce a straightforward yet effective method to empirically study memorization in deep neural networks for classification tasks. Our approach augments each training sample w…
Learned Random Label Predictions as a Neural Network Complexity Metric
Marlon Becker, Benjamin Risse
We empirically investigate the impact of learning randomly generated labels in parallel to class labels in supervised learning on memorization, model complexity, and generalization…
Probabilistic Photonic Computing with Chaotic Light
Frank Brückerhoff-Plückelmann, Hendrik Borras, Bernhard Klein +10
Biological neural networks effortlessly tackle complex computational problems and excel at predicting outcomes from noisy, incomplete data, a task that poses significant challenges…
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead
Marlon Becker, Frederick Altrock, Benjamin Risse
The recently proposed optimization algorithm for deep neural networks Sharpness Aware Minimization (SAM) suggests perturbing parameters before gradient calculation by a gradient as…
Critical nonlinear aspects of hopping transport for reconfigurable logic in disordered dopant networks
Henri Tertilt, Jonas Mensing, Marlon Becker +3
Nonlinear behavior in the hopping transport of interacting charges enables reconfigurable logic in disordered dopant network devices, where voltages applied at control electrodes t…