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pro vyhledávání: '"Gerum, Richard C."'
As convolutional neural networks (CNNs) become more accurate at object recognition, their representations become more similar to the primate visual system. This finding has inspired us and other researchers to ask if the implication also runs the oth
Externí odkaz:
http://arxiv.org/abs/2209.02582
Recent studies suggest that artificial neural networks (ANNs) that match the spectral properties of the mammalian visual cortex -- namely, the $\sim 1/n$ eigenspectrum of the covariance matrix of neural activities -- achieve higher object recognition
Externí odkaz:
http://arxiv.org/abs/2208.10576
Autor:
Gerum, Richard C., Schilling, Achim
Publikováno v:
Neural Computation (2021) 33 (10)
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 biologically inspired neuron models such as the Leaky-Integrate-and-Fire (LIF) n
Externí odkaz:
http://arxiv.org/abs/2004.13532
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 to resolve complex tasks was highly increased over the last decades. H
Externí odkaz:
http://arxiv.org/abs/1911.10988
Publikováno v:
In Neural Networks August 2020 128:305-312
Autor:
Gerum, Richard C.1 (AUTHOR) gerum@yorku.ca, Schilling, Achim2 (AUTHOR) achim.schilling@fau.de
Publikováno v:
Neural Computation. Oct2021, Vol. 33 Issue 10, p2827-2852. 26p. 1 Color Photograph, 2 Black and White Photographs, 2 Diagrams, 2 Charts, 6 Graphs.
Rheologic models consisting of combinations of linear elements, such as springs and dashpots, are widely used in biophysics to describe the mechanical and, in particular, the viscoelastic behavior of proteins, cells, tissue, and soft matter. Even sim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2091::6dc4c047664b98007db7a7f62d957ff5
https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/19374
https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/19374
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Autor:
Spörrer, Marina, Kah, Delf, Gerum, Richard C., Reischl, Barbara, Huraskin, Danyil, Dessalles, Claire A., Schneider, Werner, Goldmann, Wolfgang H., Herrmann, Harald, Thievessen, Ingo, Clemen, Christoph S., Friedrich, Oliver, Hashemolhosseini, Said, Schröder, Rolf, Fabry, Ben
Publikováno v:
Neuropathology & Applied Neurobiology; Apr2022, Vol. 48 Issue 3, p1-11, 11p
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