12 citations · 13 across the 7 of their papers we have counts for
3 papers · 1 filter
Stochastic models for online optimization
Umberto Casti, Sandro Zampieri
In this paper, we propose control-theoretic methods as tools for the design of online optimization algorithms that are able to address dynamic, noisy, and partially uncertain time-…
Firing Rate Models as Associative Memory: Excitatory-Inhibitory Balance for Robust Retrieval
Simone Betteti, Giacomo Baggio, Francesco Bullo +1
Firing rate models are dynamical systems widely used in applied and theoretical neuroscience to describe local cortical dynamics in neuronal populations. By providing a macroscopic…
Input-Driven Dynamics for Robust Memory Retrieval in Hopfield Networks
Simone Betteti, Giacomo Baggio, Francesco Bullo +1
The Hopfield model provides a mathematically idealized yet insightful framework for understanding the mechanisms of memory storage and retrieval in the human brain. This model has…