no code implementations • 24 Oct 2023 • Justin Koeln, Trevor J. Bird, Jacob Siefert, Justin Ruths, Herschel Pangborn, Neera Jain
This paper introduces zonoLAB, a MATLAB-based toolbox for set-based control system analysis using the hybrid zonotope set representation.
no code implementations • 5 Apr 2023 • Navid Hashemi, Justin Ruths, Jyotirmoy V. Deshmukh
The problem addressed by this paper is the following: Suppose we obtain an optimal trajectory by solving a control problem in the training environment, how do we ensure that the real-world system trajectory tracks this optimal trajectory with minimal amount of error in a deployment environment.
no code implementations • 5 Apr 2023 • Joshua Ortiz, Alyssa Vellucci, Justin Koeln, Justin Ruths
We show that hybrid zonotopes offer an equivalent representation of feed-forward fully connected neural networks with ReLU activation functions.
1 code implementation • 25 May 2021 • David Umsonst, Justin Ruths, Henrik Sandberg
A detector threshold that provides an acceptable false alarm rate is equivalent to a specific quantile of the detector output distribution.
no code implementations • 28 Mar 2021 • Venkatraman Renganathan, Benjamin J. Gravell, Justin Ruths, Tyler H. Summers
State estimators are crucial components of anomaly detectors that are used to monitor cyber-physical systems.
no code implementations • 22 Mar 2021 • Navid Hashemi, Mahyar Fazlyab, Justin Ruths
We exploit recent results in quantifying the robustness of neural networks to input variations to construct and tune a model-based anomaly detector, where the data-driven estimator model is provided by an autoregressive neural network.
no code implementations • 10 Dec 2020 • Navid Hashemi, Justin Ruths, Mahyar Fazlyab
Abstracting neural networks with constraints they impose on their inputs and outputs can be very useful in the analysis of neural network classifiers and to derive optimization-based algorithms for certification of stability and robustness of feedback systems involving neural networks.
no code implementations • 15 Jun 2020 • Navid Hashemi, Justin Ruths
General results on convex bodies are reviewed and used to derive an exact closed-form parametric formula for the boundary of the geometric (Minkowski) sum of $k$ ellipsoids in $n$-dimensional Euclidean space.