Search Results - "Tamborrino, Massimiliano"

Approximation of the first passage time density of a Wiener process to an exponentially decaying boundary by two-piecewise linear threshold. Application to neuronal spiking activity by Tamborrino, Massimiliano

“…The first passage time density of a diffusion process to a time varying threshold is of primary interest in different fields. Here, we consider a Brownian…”
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Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs by Buckwar, Evelyn, Tamborrino, Massimiliano, Tubikanec, Irene

“…Approximate Bayesian computation (ABC) has become one of the major tools of likelihood-free statistical inference in complex mathematical models…”
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Predictions of COVID-19 dynamics in the UK: Short-term forecasting and analysis of potential exit strategies by Keeling, Matt J, Hill, Edward M, Gorsich, Erin E, Penman, Bridget, Guyver-Fletcher, Glen, Holmes, Alex, Leng, Trystan, McKimm, Hector, Tamborrino, Massimiliano, Dyson, Louise, Tildesley, Michael J

“…Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all…”
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GParareal: a time-parallel ODE solver using Gaussian process emulation by Pentland, Kamran, Tamborrino, Massimiliano, Sullivan, T. J., Buchanan, James, Appel, L. C.

“…Sequential numerical methods for integrating initial value problems (IVPs) can be prohibitively expensive when high numerical accuracy is required over the…”
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Special Issue: Neural Coding 2018 by Kostal, Lubomir, Tamborrino, Massimiliano, Tamborrino, Massimiliano

“…The special issue is available from: https://www.aimspress.com/newsinfo/1269.html…”
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Shot noise, weak convergence and diffusion approximations by Tamborrino, Massimiliano, Lansky, Petr

“…Shot noise processes have been extensively studied due to their mathematical properties and their relevance in several applications. Here, we consider…”
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Guided Sequential ABC Schemes for Intractable Bayesian Models by Picchini, Umberto, Tamborrino, Massimiliano

“…Sequential algorithms such as sequential importance sampling (SIS) and sequential Monte Carlo (SMC) have proven fundamental in Bayesian inference for models…”
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Inference for the stochastic FitzHugh-Nagumo model from real action potential data via approximate Bayesian computation by Samson, Adeline, Tamborrino, Massimiliano, Tubikanec, Irene

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Inference for the stochastic FitzHugh-Nagumo model from real action potential data via approximate Bayesian computation by Samson, Adeline, Tamborrino, Massimiliano, Tubikanec, Irene

“…The stochastic FitzHugh-Nagumo (FHN) model considered here is a two-dimensional nonlinear stochastic differential equation with additive degenerate noise,…”
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A splitting method for SDEs with locally Lipschitz drift: Illustration on the FitzHugh-Nagumo model by Buckwar, Evelyn, Samson, Adeline, Tamborrino, Massimiliano, Tubikanec, Irene

“…In this article, we construct and analyse an explicit numerical splitting method for a class of semi-linear stochastic differential equations (SDEs) with…”
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Qualitative properties of different numerical methods for the inhomogeneous geometric Brownian motion by Tubikanec, Irene, Tamborrino, Massimiliano, Lansky, Petr, Buckwar, Evelyn

“…We provide a comparative analysis of qualitative features of different numerical methods for the inhomogeneous geometric Brownian motion (IGBM). The limit…”
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First passage times of two-dimensional correlated processes: Analytical results for the Wiener process and a numerical method for diffusion processes by Sacerdote, Laura, Tamborrino, Massimiliano, Zucca, Cristina

“…Given a two-dimensional correlated diffusion process, we determine the joint density of the first passage times of the process to some constant boundaries…”
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Inhibition enhances the coherence in the Jacobi neuronal model by D’Onofrio, Giuseppe, Lansky, Petr, Tamborrino, Massimiliano

“…•The dependence of the noise in the Jacobi neuronal model on the rate of inhibition generates non trivial behavior of some measures of spike variability.•The…”
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Weak convergence of marked point processes generated by crossings of multivariate jump processes. Applications to neural network modeling by Tamborrino, Massimiliano, Sacerdote, Laura, Jacobsen, Martin

“…We consider the multivariate point process determined by the crossing times of the components of a multivariate jump process through a multivariate boundary,…”
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Detecting dependencies between spike trains of pairs of neurons through copulas by Sacerdote, Laura, Tamborrino, Massimiliano, Zucca, Cristina

“…Abstract The dynamics of a neuron are influenced by the connections with the network where it lies. Recorded spike trains exhibit patterns due to the…”
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A review of the methods for neuronal response latency estimation by Levakova, Marie, Tamborrino, Massimiliano, Ditlevsen, Susanne, Lansky, Petr

“…Neuronal response latency is usually vaguely defined as the delay between the stimulus onset and the beginning of the response. It contains important…”
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Gaussian counter models for visual identification of briefly presented, mutually confusable single stimuli in pure accuracy tasks by Tamborrino, Massimiliano, Ditlevsen, Susanne, Markussen, Bo, Kyllingsbæk, Søren

“…When identifying confusable visual stimuli, accumulation of information over time is an obvious strategy of the observer. However, the nature of the…”
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Parameter inference from hitting times for perturbed Brownian motion by Tamborrino, Massimiliano, Ditlevsen, Susanne, Lansky, Peter

“…A latent internal process describes the state of some system, e.g. the social tension in a political conflict, the strength of an industrial component or the…”
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Leaky integrate and fire models coupled through copulas: association properties of the interspike intervals by Sacerdote, Laura, Tamborrino, Massimiliano

“…We propose a model able to describe the Interspike Intervals of two or more neurons subject to common inputs from the network. The single neuron dynamic is…”
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Guided sequential ABC schemes for intractable Bayesian models by Picchini, Umberto, Tamborrino, Massimiliano

“…Bayesian Analysis 2024 Sequential algorithms such as sequential importance sampling (SIS) and sequential Monte Carlo (SMC) have proven fundamental in Bayesian…”
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