Zobrazeno 1 - 10
of 753
pro vyhledávání: '"Diesmann, Markus"'
Autor:
Albers, Jasper, Kurth, Anno C., Gutzen, Robin, Morales-Gregorio, Aitor, Denker, Michael, Grün, Sonja, van Albada, Sacha J., Diesmann, Markus
Assessing the similarity of matrices is valuable for analyzing the extent to which data sets exhibit common features in tasks such as data clustering, dimensionality reduction, pattern recognition, group comparison, and graph analysis. Methods propos
Externí odkaz:
http://arxiv.org/abs/2403.17687
Autor:
Korcsak-Gorzo, Agnes, Linssen, Charl, Albers, Jasper, Dasbach, Stefan, Duarte, Renato, Kunkel, Susanne, Morrison, Abigail, Senk, Johanna, Stapmanns, Jonas, Tetzlaff, Tom, Diesmann, Markus, van Albada, Sacha J.
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for empirical data in mathematical models, implement such models in software
Externí odkaz:
http://arxiv.org/abs/2212.05354
Autor:
Bouhadjar, Younes, Siegel, Sebastian, Tetzlaff, Tom, Diesmann, Markus, Waser, Rainer, Wouters, Dirk J.
Brain-inspired computing proposes a set of algorithmic principles that hold promise for advancing artificial intelligence. They endow systems with self learning capabilities, efficient energy usage, and high storage capacity. A core concept that lies
Externí odkaz:
http://arxiv.org/abs/2211.16592
Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A particular type o
Externí odkaz:
http://arxiv.org/abs/2206.10538
Autor:
Albers, Jasper, Pronold, Jari, Kurth, Anno Christopher, Vennemo, Stine Brekke, Mood, Kaveh Haghighi, Patronis, Alexander, Terhorst, Dennis, Jordan, Jakob, Kunkel, Susanne, Tetzlaff, Tom, Diesmann, Markus, Senk, Johanna
Publikováno v:
Front. Neuroinform. 16:837549 (2022)
Modern computational neuroscience strives to develop complex network models to explain dynamics and function of brains in health and disease. This process goes hand in hand with advancements in the theory of neuronal networks and increasing availabil
Externí odkaz:
http://arxiv.org/abs/2112.09018
Publikováno v:
Neuromorph. Comput. Eng. 2 021001 (2022)
Full scale simulations of neuronal network models of the brain are challenging due to the high density of connections between neurons. This contribution reports run times shorter than the simulated span of biological time for a full scale model of th
Externí odkaz:
http://arxiv.org/abs/2111.04398
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervi
Externí odkaz:
http://arxiv.org/abs/2111.03456
Autor:
Senk, Johanna, Kriener, Birgit, Djurfeldt, Mikael, Voges, Nicole, Jiang, Han-Jia, Schüttler, Lisa, Gramelsberger, Gabriele, Diesmann, Markus, Plesser, Hans E., van Albada, Sacha J.
Publikováno v:
PLoS Comput Biol 18(9): e1010086 (2022)
Sustainable research on computational models of neuronal networks requires published models to be understandable, reproducible, and extendable. Missing details or ambiguities about mathematical concepts and assumptions, algorithmic implementations, o
Externí odkaz:
http://arxiv.org/abs/2110.02883
Autor:
Pronold, Jari, Jordan, Jakob, Wylie, Brian J. N., Kitayama, Itaru, Diesmann, Markus, Kunkel, Susanne
Simulation is a third pillar next to experiment and theory in the study of complex dynamic systems such as biological neural networks. Contemporary brain-scale networks correspond to directed graphs of a few million nodes, each with an in-degree and
Externí odkaz:
http://arxiv.org/abs/2109.12855
Autor:
Pronold, Jari, Jordan, Jakob, Wylie, Brian J. N., Kitayama, Itaru, Diesmann, Markus, Kunkel, Susanne
Generic simulation code for spiking neuronal networks spends the major part of time in the phase where spikes have arrived at a compute node and need to be delivered to their target neurons. These spikes were emitted over the last interval between co
Externí odkaz:
http://arxiv.org/abs/2109.11358