2 citations · 2 across the 9 of their papers we have counts for
10 papers
Exploring Clustering Capability of Inpainting Model Embeddings for Pattern-based Individual Identification
Jens van Bijsterveld, Daniele Avitabile, Fons J. Verbeek +1
In this paper, we explore deep learning techniques for individual identification of animals based on their skin patterns. Individual identification is crucial in biodiversity monit…
State and Parameter Estimation for a Neural Model of Local Field Potentials
Daniele Avitabile, Gabriel J. Lord, Khadija Meddouni
The study of cortical dynamics during different states such as decision making, sleep and movement, is an important topic in Neuroscience. Modelling efforts aim to relate the neura…
Guided filtering and smoothing for infinite-dimensional diffusions
Thorben Pieper-Sethmacher, Daniele Avitabile, Frank van der Meulen
We consider the filtering and smoothing problems for an infinite-dimensional diffusion process X, observed through a finite-dimensional representation at discrete points in time. A…
Stochastic collocation schemes for Neural Field Equations with random data
Daniele Avitabile, Francesca Cavallini, Svetlana Dubinkina +1
We develop and analyse numerical schemes for uncertainty quantification in neural field equations subject to random parametric data in the synaptic kernel, firing rate, external st…
Neural Field Equations with random data
Daniele Avitabile, Francesca Cavallini, Svetlana Dubinkina +1
We study neural field equations, which are prototypical models of large-scale cortical activity, subject to random data. We view this spatially-extended, nonlocal evolution equatio…
Radial Basis Function Techniques for Neural Field Models on Surfaces
Sage B Shaw, Zachary P Kilpatrick, Daniele Avitabile
We present a numerical framework for solving neural field equations on surfaces using Radial Basis Function (RBF) interpolation and quadrature. Neural field models describe the evo…
Poisson Hypothesis and large-population limit for networks of spiking neurons
Daniele Avitabile, Michel Davydov
We study mean-field descriptions for spatially-extended networks of linear (leaky) and quadratic integrate-and-fire neurons with stochastic spiking times. We consider large-populat…
Neural Fields and Noise-Induced Patterns in Neurons on Large Disordered Networks
Daniele Avitabile, James MacLaurin
We study pattern formation in class of a large-dimensional neural networks posed on random graphs and subject to spatio-temporal stochastic forcing. Under generic conditions on cou…
Well-posedness and regularity of solutions to neural field problems with dendritic processing
Daniele Avitabile, Nikolai V. Chemetov, Pedro M. Lima
We study solutions to a recently proposed neural field model in which dendrites are modelled as a continuum of vertical fibres stemming from a somatic layer. Since voltage propagat…
Bump attractors and waves in networks of leaky integrate-and-fire neurons
D. Avitabile, J. L. Davis, K. C. A. Wedgwood
Bump attractors are wandering localised patterns observed in in vivo experiments of spatially-extended neurobiological networks. They are important for the brain's navigational sys…