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: The information content of artificial neuronal networks can be saved in precise bits, yet no such number has ever made sense for biological neuronal networks. Not only the number, even what parameters should be
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: The information content of artificial neuronal networks can be saved in precise bits, yet no such number has ever made sense for biological neuronal networks. Not only the number, even what parameters should be
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Data Management concentrates on the methodology of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data on large scales. We put emphasis on methods
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can be saved in precise bits, yet no such number has ever made sense for biological neuronal networks. Not only the number, even what parameters should be quantified remains unclear – a true unknown
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and management data, time series, long-term field experiments, geospatial data such as remote sensing) - Knowledge of research data management, metadata and data publication standards relevant
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compressed sensing) to determine greenhouse gas and pollutant emissions in cities using atmospheric measurements (MUCCnet: https://atmosphere.ei.tum.de/ ) and in-situ sensor networks in ICOS Cities project