Results 11 to 20 of about 30,785,448 (215)
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 ...
C. Hirsch, B. Jahnel, E. Cali
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Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information [PDF]
Knowledge Discovery and Data Mining, 2019 Predicting when and where events will occur in cities, like taxi pick-ups, crimes, and vehicle collisions, is a challenging and important problem with many applications in fields such as urban planning, transportation optimization and location-based ...
Maya Okawa +5 more
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Point processes with Gaussian boson sampling. [PDF]
Physical Review E, 2019 Random point patterns are ubiquitous in nature, and statistical models such as point processes, i.e., algorithms that generate stochastic collections of points, are commonly used to simulate and interpret them.
S. Jahangiri +3 more
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Revealing Spectrum Features of Stochastic Neuron Spike Trains
Mathematics, 2020 Power spectra of spike trains reveal important properties of neuronal behavior. They exhibit several peaks, whose shape and position depend on applied stimuli and intrinsic biophysical properties, such as input current density and channel noise.
Simone Orcioni +3 more
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DECOMPOSING IMAGES INTO TRIANGLES BY DELAUNAY POINT PROCESSES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 We propose a method for decomposing images into triangles. Contrary to superpixel methods, our output representation both preserves the geometric information disseminated in input images, and has an attractive storage capacity.
D. Chai
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Rank-Based Mixture Models for Temporal Point Processes
Frontiers in Applied Mathematics and Statistics, 2022 Temporal point process, an important area in stochastic process, has been extensively studied in both theory and applications. The classical theory on point process focuses on time-based framework, where a conditional intensity function at each given ...
Yang Chen, Yijia Ma, Wei Wu
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A Variational Auto-Encoder Model for Stochastic Point Processes [PDF]
Computer Vision and Pattern Recognition, 2019 We propose a novel probabilistic generative model for action sequences. The model is termed the Action Point Process VAE (APP-VAE), a variational auto-encoder that can capture the distribution over the times and categories of action sequences.
Nazanin Mehrasa +5 more
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Axioms, 2020 A plethora of applications from mathematical programming, such as minimax, and mathematical programming, penalization, fixed point to mention a few can be framed as equilibrium problems.
Nopparat Wairojjana +3 more
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Poisson Cox Point Processes for Vehicular Networks [PDF]
IEEE Transactions on Vehicular Technology, 2018 This paper analyzes statistical properties of the Poisson line Cox point process useful in the modeling of vehicular networks. The point process is created by a two-stage construction: a Poisson line process to model road infrastructure and independent ...
Chang-Sik Choi, F. Baccelli
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DETECTING LINEAR FEATURES BY SPATIAL POINT PROCESSES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 This paper proposes a novel approach for linear feature detection. The contribution is twofold: a novel model for spatial point processes and a new method for linear feature detection.
D. Chai, A. Schmidt, C. Heipke
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