activity
20182022
most citedAdvanced sleep spindle identification with neural networks

45 citations · 70 across the 3 of their papers we have counts for

collaborators

5 papers

eess.SP202245 cited

Advanced sleep spindle identification with neural networks

Lars Kaulen, Justus T. C. Schwabedal, Jules Schneider +2

Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroe…

q-bio.QM202125 cited

Automated scoring of pre-REM sleep in mice with deep learning

Niklas Grieger, Justus T. C. Schwabedal, Stefanie Wendel +2

Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems,…

cs.LG2020

Differentially Private Generation of Small Images

Justus T. C. Schwabedal, Pascal Michel, Mario S. Riontino

We explore the training of generative adversarial networks with differential privacy to anonymize image data sets. On MNIST, we numerically measure the privacy-utility trade-off us…

q-bio.QM2018

Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning

Justus T. C. Schwabedal, Daniel Sippel, Moritz D. Brandt +1

Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-ter…

eess.SP2018

Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates

Justus T. C. Schwabedal, John C. Snyder, Ayse Cakmak +2

Randomizing the Fourier-transform (FT) phases of temporal-spatial data generates surrogates that approximate examples from the data-generating distribution. We propose such FT surr…