61 citations · 266 across the 10 of their papers we have counts for
10 papers
Improving the Accuracy and Robustness of CNNs Using a Deep CCA Neural Data Regularizer
Cassidy Pirlot, Richard C. Gerum, Cory Efird +2
As convolutional neural networks (CNNs) become more accurate at object recognition, their representations become more similar to the primate visual system. This finding has inspire…
Different Spectral Representations in Optimized Artificial Neural Networks and Brains
Richard C. Gerum, Cassidy Pirlot, Alona Fyshe +1
Recent studies suggest that artificial neural networks (ANNs) that match the spectral properties of the mammalian visual cortex -- namely, the eigenspectrum of the covar…
Predictive coding and stochastic resonance as fundamental principles of auditory perception
Achim Schilling, William Sedley, Richard Gerum +7
How is information processed in the brain during perception? Mechanistic insight is achieved only when experiments are employed to test formal or computational models. In analogy t…
Integration of Leaky-Integrate-and-Fire-Neurons in Deep Learning Architectures
Richard C. Gerum, Achim Schilling
Up to now, modern Machine Learning is mainly based on fitting high dimensional functions to enormous data sets, taking advantage of huge hardware resources. We show that biological…
Sparsity through evolutionary pruning prevents neuronal networks from overfitting
Richard C. Gerum, André Erpenbeck, Patrick Krauss +1
Modern Machine learning techniques take advantage of the exponentially rising calculation power in new generation processor units. Thus, the number of parameters which are trained…
pylustrator: Code generation for reproducible figures for publication
Richard Gerum
One major challenge in science is to make all results potentially reproducible. Thus, along with the raw data, every step from basic processing of the data, evaluation, to the gene…
Objective estimation of sensory thresholds based on neurophysiological parameters
Achim Schilling, Richard Gerum, Patrick Krauss +3
Reliable determination of sensory thresholds is the holy grail of signal detection theory. However, there exists no gold standard for the estimation of thresholds based on neurophy…
How deep is deep enough? -- Quantifying class separability in the hidden layers of deep neural networks
Achim Schilling, Claus Metzner, Jonas Rietsch +3
Deep neural networks typically outperform more traditional machine learning models in their ability to classify complex data, and yet is not clear how the individual hidden layers…
Open(G)PIAS: An open source solution for the construction of a high-precision Acoustic-Startle-Response (ASR) setup for tinnitus screening and threshold estimation in rodents
Richard Gerum, Hinrich Rahlfs, Matthias Streb +7
The acoustic startle reflex (ASR) that can be induced by a loud sound stimulus can be used as a versatile tool to, e.g., estimate hearing thresholds or identify subjective tinnitus…
CameraTransform: a Scientific Python Package for Perspective Camera Corrections
Richard Gerum, Sebastian Richter, Alexander Winterl +2
Scientific applications often require an exact reconstruction of object positions and distances from digital images. Therefore, the images need to be corrected for perspective dist…