Results 1 to 10 of about 28,661,875 (311)
Continuum percolation for Cox point processes [PDF]
Stochastic Processes and their Applications, 2017 We investigate continuum percolation for Cox point processes, that is, Poisson point processes driven by random intensity measures. First, we derive sufficient conditions for the existence of non-trivial sub- and super-critical percolation regimes based ...
Cali, Elie +2 more
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Deconvolution of calcium imaging data using marked point processes. [PDF]
PLoS Computational Biology, 2020 Calcium imaging has been widely used for measuring spiking activities of neurons. When using calcium imaging, we need to extract summarized information from the raw movie beforehand.
Ryohei Shibue, Fumiyasu Komaki
doaj +2 more sources
Spatio-temporal Diffusion Point Processes [PDF]
Knowledge Discovery and Data Mining, 2023 Spatio-temporal point process (STPP) is a stochastic collection of events accompanied with time and space. Due to computational complexities, existing solutions for STPPs compromise with conditional independence between time and space, which consider the
Yuan Yuan +4 more
semanticscholar +1 more source
Neural Temporal Point Processes: A Review [PDF]
International Joint Conference on Artificial Intelligence, 2021 Temporal point processes (TPP) are probabilistic generative models for continuous-time event sequences. Neural TPPs combine the fundamental ideas from point process literature with deep learning approaches, thus enabling construction of flexible and ...
Oleksandr Shchur +3 more
semanticscholar +1 more source
A Monad for Probabilistic Point Processes [PDF]
ACT, 2021 A point process on a space is a random bag of elements of that space. In this paper we explore programming with point processes in a monadic style. To this end we identify point processes on a space X with probability measures of bags of elements in X ...
Swaraj Dash, S. Staton
semanticscholar +1 more source
Determinantal Point Processes in Randomized Numerical Linear Algebra [PDF]
Notices of the American Mathematical Society, 2020 Randomized Numerical Linear Algebra (RandNLA) uses randomness to develop improved algorithms for matrix problems that arise in scientific computing, data science, machine learning, etc. Determinantal Point Processes (DPPs), a seemingly unrelated topic in
Michal Derezinski, Michael W. Mahoney
semanticscholar +1 more source
Information criteria for inhomogeneous spatial point processes [PDF]
Australian & New Zealand journal of statistics (Print), 2020 The theoretical foundation for a number of model selection criteria is established in the context of inhomogeneous point processes and under various asymptotic settings: infill, increasing domain and combinations of these.
Achmad Choiruddin +2 more
semanticscholar +1 more source
Rain process models and convergence to point processes [PDF]
Nonlinear Processes in Geophysics, 2023 A variety of stochastic models have been used to describe time series of precipitation or rainfall. Since many of these stochastic models are simplistic, it is desirable to develop connections between the stochastic models and the underlying physics of ...
S. Hottovy, S. N. Stechmann
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Point Processes in a Metric Space and Their Applications
Mathematics, 2022 Point processes are important in extreme value theory due to their equivalent formulations of two popular models in various applications: the block maxima models and the peak-over-threshold model.
Yuwei Zhao
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Further results on why a point process is effective for estimating correlation between brain regions
Papers in Physics, 2020 Signals from brain functional magnetic resonance imaging (fMRI) can be efficiently represented by a sparse spatiotemporal point process, according to a recently introduced heuristic signal processing scheme.
I. Cifre +4 more
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