A Marked Point Process Framework for Extracellular Electrical Potentials [PDF]
Frontiers in Systems Neuroscience, 2017 Neuromodulations are an important component of extracellular electrical potentials (EEP), such as the Electroencephalogram (EEG), Electrocorticogram (ECoG) and Local Field Potentials (LFP).
Carlos A. Loza +2 more
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Design as a Marked Point Process [PDF]
Journal of Mechanical Design, 2021 Abstract Although artificial intelligence (AI) systems which support composition using predictive text are well established, there are no analogous technologies for mechanical design. Motivated by the vision of a predictive system that learns from previous designs and can interactively provide a list of established feature alternatives ...
Quigley, John +4 more
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Marked point process variational autoencoder with applications to unsorted spiking activities. [PDF]
PLoS Computational BiologySpike train modeling across large neural populations is a powerful tool for understanding how neurons code information in a coordinated manner. Recent studies have employed marked point processes in neural population modeling. The marked point process is
Ryohei Shibue, Tomoharu Iwata
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A common goodness-of-fit framework for neural population models using marked point process time-rescaling. [PDF]
J Comput Neurosci, 2018 A critical component of any statistical modeling procedure is the ability to assess the goodness-of-fit between a model and observed data. For spike train models of individual neurons, many goodness-of-fit measures rely on the time-rescaling theorem and ...
Tao L, Weber KE, Arai K, Eden UT.
europepmc +2 more sources
A Marked Point Process Filtering Approach for Tracking Sympathetic Arousal From Skin Conductance
IEEE Access, 2020 Human emotion represents a complex neural process within the brain. The ability to automatically recognize emotions from physiological signals has the potential to impact humanity in multiple ways through applications in human-machine interaction, remote
Dilranjan S. Wickramasuriya +1 more
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Clusterless Decoding of Position from Multiunit Activity Using a Marked Point Process Filter. [PDF]
Neural Comput, 2015 Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally these methods assume that multiunit spiking activity has already been correctly spike-sorted.
Deng X +4 more
europepmc +2 more sources
FACADE INTERPRETATION USING A MARKED POINT PROCESS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Our objective is the interpretation of facade images in a top-down manner, using a Markov marked point process formulated as a Gibbs process. Given single rectified facade images, we aim at the accurate detection of relevant facade objects as windows and
S. Wenzel, W. Förstner
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Fitting three-dimensional Laguerre tessellations by hierarchical marked point process models [PDF]
Spatial Statistics, 2021 We present a general statistical methodology for analysing a Laguerre tessellation data set viewed as a realization of a marked point process model. In the first step, for the points we use a nested sequence of multiscale processes which constitute a ...
F. Seitl, Jesper Møller, V. Beneš
semanticscholar +1 more source
Multiple objects detection in biological images using a marked point process framework
Methods, 2017 X. Descombes
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Rescaling Marked Point Processes [PDF]
Australian <html_ent glyph="@amp;" ascii="&"/> New Zealand Journal of Statistics, 2004 From the authors' abstract: \textit{P.-A. Meyer} [in: Sém. Bourbaki 1968/69, No. 361, 245--259 (1971; Zbl 0273.60053)] showed how to use the compensator to rescale a multivariate point process, forming independent Poisson processes with intensity 1. Meyer's result has been generalized to multidimensional point processes.
David Vere-Jones +1 more
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