Materials and devices as solutions to computational problems in machine learning
The growth of machine learning, combined with the approaching limits of conventional
digital computing, are driving a search for alternative and complementary forms of …
digital computing, are driving a search for alternative and complementary forms of …
An overview of neuromorphic computing for artificial intelligence enabled hardware-based hopfield neural network
Compared with von Neumann's computer architecture, neuromorphic systems offer more
unique and novel solutions to the artificial intelligence discipline. Inspired by biology, this …
unique and novel solutions to the artificial intelligence discipline. Inspired by biology, this …
Phase transitions and self-organized criticality in networks of stochastic spiking neurons
Phase transitions and critical behavior are crucial issues both in theoretical and
experimental neuroscience. We report analytic and computational results about phase …
experimental neuroscience. We report analytic and computational results about phase …
On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs
F Gerhard, M Deger, W Truccolo - PLoS computational biology, 2017 - journals.plos.org
Point process generalized linear models (PP-GLMs) provide an important statistical
framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic …
framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic …
Republished: Dynamics of stochastic integrate-and-fire networks
GK Ocker - Physical Review X, 2023 - APS
The neural dynamics generating sensory, motor, and cognitive functions are commonly
understood through field theories for neural population activity. Classic neural field theories …
understood through field theories for neural population activity. Classic neural field theories …
Hydrodynamic limit for interacting neurons
This paper studies the hydrodynamic limit of a stochastic process describing the time
evolution of a system with N neurons with mean-field interactions produced both by …
evolution of a system with N neurons with mean-field interactions produced both by …
On a toy model of interacting neurons
N Fournier, E Löcherbach - 2016 - projecteuclid.org
We continue the study of a stochastic system of interacting neurons introduced in De Masi,
Galves, Löcherbach and Presutti (J. Stat. Phys. 158 (2015) 866–902). The system consists of …
Galves, Löcherbach and Presutti (J. Stat. Phys. 158 (2015) 866–902). The system consists of …
Hawkes processes on large networks
S Delattre, N Fournier, M Hoffmann - 2016 - projecteuclid.org
We generalise the construction of multivariate Hawkes processes to a possibly infinite
network of counting processes on a directed graph G. The process is constructed as the …
network of counting processes on a directed graph G. The process is constructed as the …
Synaptic balance due to homeostatically self-organized quasicritical dynamics
Recent experiments suggested that a homeostatic regulation of synaptic balance leads the
visual system to recover and maintain a regime of power-law avalanches. Here we study an …
visual system to recover and maintain a regime of power-law avalanches. Here we study an …
Mechanisms of self-organized quasicriticality in neuronal network models
O Kinouchi, R Pazzini, M Copelli - Frontiers in Physics, 2020 - frontiersin.org
The critical brain hypothesis states that there are information processing advantages for
neuronal networks working close to the critical region of a phase transition. If this is true, we …
neuronal networks working close to the critical region of a phase transition. If this is true, we …