6 citations · 6 across the 4 of their papers we have counts for
6 papers · 1 filter
Frequency Domain Gaussian Process Models for Uncertainties
Alex Devonport, Peter Seiler, Murat Arcak
Complex-valued Gaussian processes are used in Bayesian frequency-domain system identification as prior models for regression. If each realization of such a process were an $H_\inft…
DaDRA: A Python Library for Data-Driven Reachability Analysis
Jared Mejia, Alex Devonport, Murat Arcak
Reachability analysis is used to determine all possible states that a system acting under uncertainty may reach. It is a critical component to obtain guarantees of various safety-c…
Data-Driven Reachability Analysis with Christoffel Functions
Alex Devonport, Forest Yang, Laurent El Ghaoui +1
We present an algorithm for data-driven reachability analysis that estimates finite-horizon forward reachable sets for general nonlinear systems using level sets of a certain class…
Bayesian Safe Learning and Control with Sum-of-Squares Analysis and Polynomial Kernels
Alex Devonport, He Yin, Murat Arcak
We propose an iterative method to safely learn the unmodeled dynamics of a nonlinear system using Bayesian Gaussian process (GP) models with polynomial kernel functions. The method…
PIRK: Scalable Interval Reachability Analysis for High-Dimensional Nonlinear Systems
Alex Devonport, Mahmoud Khaled, Murat Arcak +1
Reachability analysis is a critical tool for the formal verification of dynamical systems and the synthesis of controllers for them. Due to their computational complexity, many rea…
Data-Driven Reachable Set Computation using Adaptive Gaussian Process Classification and Monte Carlo Methods
Alex Devonport, Murat Arcak
We present two data-driven methods for estimating reachable sets with probabilistic guarantees. Both methods make use of a probabilistic formulation allowing for a formal definitio…