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Reed, Robert (author), Laurenti, L. (author), Lahijanian, Morteza (author)Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising tool to learn and control complex dynamical systems. In this letter, we develop a scalable abstraction-based framework that enables the use of DKL for control...journal article 2023
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Skovbekk, John (author), Laurenti, L. (author), Frew, Eric (author), Lahijanian, Morteza (author)Verifying the performance of safety-critical, stochastic systems with complex noise distributions is difficult. We introduce a general procedure for the finite abstraction of nonlinear stochastic systems with nonstandard (e.g., non-affine, non-symmetric, non-unimodal) noise distributions for verification purposes. The method uses a finite...journal article 2023
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Jafarian, M. (author), Mamduhi, Mohammad H. (author), Johansson, Karl H. (author)This article studies stochastic relative phase stability, i.e., stochastic phase-cohesiveness, of discrete-time phase-coupled oscillators. The stochastic phase-cohesiveness in two types of networks is studied. First, we consider oscillators coupled with 2π-periodic odd functions over underlying undirected graphs subject to both multiplicative...journal article 2023