7 papers
Geometric SSM: LTI State Space Models for Selective Tasks
Umberto Casti, Giacomo Baggio, Sandro Zampieri +1
A key claim in recent work on Selective State Space Models is that selectivity, the ability to focus on relevant information while filtering irrelevant inputs, requires breaking th…
A Dynamical Theory of Sequential Retrieval in Input-Driven Hopfield Networks
Simone Betteti, Giacomo Baggio, Sandro Zampieri
Reasoning is the ability to integrate internal states and external inputs in a meaningful and semantically consistent flow. Contemporary machine learning (ML) systems increasingly…
Anti-windup design for internal model online constrained optimization
Umberto Casti, Sandro Zampieri
This paper proposes a novel algorithmic design procedure for online constrained optimization grounded in control-theoretic principles. By integrating the Internal Model Principle (…
Controllable Neural Architectures for Multi-Task Control
Umberto Casti, Giacomo Baggio, Sandro Zampieri +1
This paper studies a multi-task control problem where multiple linear systems are to be regulated by a single non-linear controller. In particular, motivated by recent advances in…
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…