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Found 8 papers, 4 papers with code
Available observation time regulates optimal balance between sensitivity and confidence
Tasks that require information about the world imply a trade-off between the time spent on observation and the variance of the response.
Signatures of hierarchical temporal processing in the mouse visual system
A core challenge for the brain is to process information across various timescales.
Tackling the subsampling problem to infer collective properties from limited data
However, despite the development of large-scale data-acquisition techniques, experimental observations are often limited to a tiny fraction of the system.
Autocorrelations from emergent bistability in homeostatic spiking neural networks on neuromorphic hardware
The extent of memory about past inputs is commonly quantified by the autocorrelation time of collective dynamics.
Modular architecture facilitates noise-driven control of synchrony in neuronal networks
Brain functions require both segregated processing of information in specialized circuits, as well as integration across circuits to perform high-level information processing.
Inferring COVID-19 spreading rates and potential change points for case number forecasts
As COVID-19 is rapidly spreading across the globe, short-term modeling forecasts provide time-critical information for decisions on containment and mitigation strategies.
Description of spreading dynamics by microscopic network models and macroscopic branching processes can differ due to coalescence
Spreading processes are conventionally monitored on a macroscopic level by counting the number of incidences over time.
Neurons and Cognition Disordered Systems and Neural Networks Physics and Society
Tailored ensembles of neural networks optimize sensitivity to stimulus statistics
The dynamic range of stimulus processing in living organisms is much larger than a single neural network can explain.
Disordered Systems and Neural Networks Neurons and Cognition
