24 citations · 42 across the 16 of their papers we have counts for
20 papers
Model Predictive Control of Spreading Processes via Sparse Resource Allocation
Ruigang Wang, Armaghan Zafar, Ian R. Manchester
In this paper, we propose a model predictive control (MPC) method for real-time intervention of spreading processes, such as epidemics and wildfire, over large-scale networks. The…
Multi-Stage Sparse Resource Allocation for Control of Spreading Processes over Networks
Vera L. J. Somers, Ian R. Manchester
In this paper we propose a method for sparse dynamic allocation of resources to bound the risk of spreading processes, such as epidemics and wildfires, using convex optimization an…
Learning Stable Koopman Embeddings
Fletcher Fan, Bowen Yi, David Rye +2
In this paper, we present a new data-driven method for learning stable models of nonlinear systems. Our model lifts the original state space to a higher-dimensional linear manifold…
Contraction-Based Methods for Stable Identification and Robust Machine Learning: a Tutorial
Ian R. Manchester, Max Revay, Ruigang Wang
This tutorial paper provides an introduction to recently developed tools for machine learning, especially learning dynamical systems (system identification), with stability and rob…
Distributed Identification of Contracting and/or Monotone Network Dynamics
Max Revay, Jack Umenberger, Ian R. Manchester
This paper proposes methods for identification of large-scale networked systems with guarantees that the resulting model will be contracting -- a strong form of nonlinear stability…
Minimizing the Risk of Spreading Processes via Surveillance Schedules and Sparse Control
Vera L. J. Somers, Ian R. Manchester
In this paper, we propose an optimization framework that combines surveillance schedules and sparse control to bound the risk of spreading processes such as epidemics and wildfires…