50 citations · 116 across the 18 of their papers we have counts for
19 papers
Learning infinite context windows in recurrent architectures via spatial neural computing
Aleix Salvador-Pomarol, Arthur N. Montanari, Earl K. Miller +2
Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-range dependencies due to va…
Disorder-promoted stability
Arthur N. Montanari, Pietro Zanin, Adilson E. Motter
Previous studies of network dynamics have suggested that heterogeneity among nodes inhibits stability, at odds with the ubiquity of inherently heterogeneous natural and engineered…
Generalized Master Stability of Heterogeneous Delay-Coupled Networks
Ana Elisa D. Barioni, Arthur N. Montanari, Adilson E. Motter
Time delays are ubiquitous in physical and biological networked systems, playing a fundamental role in the emergence and stability of collective behavior. Yet, existing theoretical…
Experimental Kuramoto Platform
Leandro Freitas, Victor H. S. Bittencourt, Débora D. Superbi +3
Phase reduction provides a principled relationship between high-dimensional oscillator dynamics and low-dimensional phase models such as the Kuramoto model. However, connecting ana…
Rethinking the green power grid for stability, not just for climate
Yiming Wang, Arthur N. Montanari, Adilson E. Motter
The 2025 Iberian blackout has renewed concerns about the resilience of power grids with high shares of renewable generation. This commentary argues that renewable generation can no…
Energy-Based Dynamical Models for Neurocomputation, Learning, and Optimization
Arthur N. Montanari, Francesco Bullo, Dmitry Krotov +1
Recent advances at the intersection of control theory, neuroscience, and machine learning have revealed novel mechanisms by which dynamical systems perform computation. These advan…
Interpretable disorder-promoted synchronization and coherence in coupled laser networks
Ana Elisa D. Barioni, Arthur N. Montanari, Adilson E. Motter
Coupled lasers offer a promising approach to scaling the power output of photonic devices for applications demanding high frequency precision and beam coherence. However, maintaini…
Distributed Lyapunov Functions for Nonlinear Networks
Yiming Wang, Arthur N. Montanari, Adilson E. Motter
Nonlinear networks are often multistable, exhibiting coexisting stable states with competing regions of attraction (ROAs). As a result, ROAs can have complex "tentacle-like" morpho…
Global Optimization Through Heterogeneous Oscillator Ising Machines
Ahmed Allibhoy, Arthur N. Montanari, Fabio Pasqualetti +1
Oscillator Ising machines (OIMs) are networks of coupled oscillators that seek the minimum energy state of an Ising model. Since many NP-hard problems are equivalent to the minimiz…
Optimal flock formation induced by agent heterogeneity
Arthur N. Montanari, Ana Elisa D. Barioni, Chao Duan +1
The study of flocking in biological systems has identified conditions for self-organized collective behavior, inspiring the development of decentralized strategies to coordinate th…
SODAs: Sparse Optimization for the Discovery of Differential and Algebraic Equations
Manu Jayadharan, Christina Catlett, Arthur N. Montanari +1
Differential-algebraic equations (DAEs) integrate ordinary differential equations (ODEs) with algebraic constraints, providing a fundamental framework for developing models of dyna…
Identifiability of Differential-Algebraic Systems
Arthur N. Montanari, François Lamoline, Robert Bereza +1
Data-driven modeling of dynamical systems often faces numerous data-related challenges. A fundamental requirement is the existence of a unique set of parameters for a chosen model…
On the Popov-Belevitch-Hautus tests for functional observability and output controllability
Arthur N. Montanari, Chao Duan, Adilson E. Motter
Functional observability and output controllability are properties that establish the conditions for the partial estimation and partial control of the system state, respectively. I…
Duality between controllability and observability for target control and estimation in networks
Arthur N. Montanari, Chao Duan, Adilson E. Motter
Output controllability and functional observability are properties that enable, respectively, the control and estimation of part of the state vector. These notions are of utmost im…
Target Controllability and Target Observability of Structured Network Systems
Arthur N. Montanari, Chao Duan, Adilson E. Motter
The duality between controllability and observability enables methods developed for full-state control to be applied to full-state estimation, and vice versa. In applications in wh…
Functional observability and subspace reconstruction in nonlinear systems
Arthur N. Montanari, Leandro Freitas, Daniele Proverbio +1
Time-series analysis is fundamental for modeling and predicting dynamical behaviors from time-ordered data, with applications in many disciplines such as physics, biology, finance,…
Buffering variability in cell regulation motifs close to criticality
Daniele Proverbio, Arthur N. Montanari, Alexander Skupin +1
Bistable biological regulatory systems need to cope with stochastic noise to fine-tune their function close to bifurcation points. Here, we study stability properties of this regim…
Functional observability and target state estimation in large-scale networks
Arthur N. Montanari, Chao Duan, Luis A. Aguirre +1
The quantitative understanding and precise control of complex dynamical systems can only be achieved by observing their internal states via measurement and/or estimation. In large-…
Particle filtering of dynamical networks: Highlighting observability issues
Arthur N. Montanari, Luis A. Aguirre
In a network of high-dimensionality, it is not feasible to measure every single node. Thus, an important goal in the literature is to define the optimal choice of sensor nodes that…