8 citations · 8 across the 9 of their papers we have counts for
11 papers
Sample Complexity of Equivariant Reinforcement Learning
Rayan Mazouz, Haibo Zhao, Chris Hillar +1
Reinforcement learning (RL) is a powerful framework for robotic control, yet its practical application is often hindered by high sample complexity. This is particularly restrictive…
Continuous-Time Gaussian Belief Trees for Motion Planning
Rayan Mazouz, Qi Heng Ho, Zachary N. Sunberg +1
We address sampling-based motion planning for continuous-time stochastic systems under process and measurement uncertainty, with probabilistic guarantees on safety and performance.…
Modeling and Control for Distributed Measurements of the Earth's Energy Imbalance
Rayan Mazouz, Marco Quadrelli, Rashied Amini +3
This paper presents a modeling and control framework for distributed systems in low Earth orbit, with the scientific objective of obtaining high accuracy estimates of the Earth's E…
Stochastic Barrier Certificates in the Presence of Dynamic Obstacles
Rayan Mazouz, Luca Laurenti, Morteza Lahijanian
In this work, we focus on safety verification of stochastic systems in dynamic environments. We introduce both time-invariant and time-varying barrier certificates for discrete-tim…
Suppressed excitonic effects enable high mobility, high-yield photoconductivity in a two-dimensional polymer crystal with axial pyridine coordination
Shuai Fu, Ye Yang, Guoquan Gao +8
Two-dimensional polymers (2DPs) and their layer-stacked covalent organic frameworks (2D COFs) offer modular, atomically precise platforms for organic optoelectronics, yet their pho…
StochasticBarrier.jl: A Toolbox for Stochastic Barrier Function Synthesis
Rayan Mazouz, Frederik Baymler Mathiesen, Luca Laurenti +1
We present StochasticBarrier.jl, an open-source Julia-based toolbox for generating Stochastic Barrier Functions (SBFs) for safety verification of discrete-time stochastic systems w…
Piecewise Control Barrier Functions for Stochastic Systems
Rayan Mazouz, Luca Laurenti, Morteza Lahijanian
This paper presents a method for the simultaneous synthesis of a barrier certificate and a safe controller for discrete-time nonlinear stochastic systems. Our approach, based on pi…
Data-Driven Permissible Safe Control with Barrier Certificates
Rayan Mazouz, John Skovbekk, Frederik Baymler Mathiesen +3
This paper introduces a method of identifying a maximal set of safe strategies from data for stochastic systems with unknown dynamics using barrier certificates. The first step is…
Piecewise Stochastic Barrier Functions
Rayan Mazouz, Frederik Baymler Mathiesen, Luca Laurenti +1
This paper presents a novel stochastic barrier function (SBF) framework for safety analysis of stochastic systems based on piecewise (PW) functions. We first outline a general form…
Feasibility-Guided Safety-Aware Model Predictive Control for Jump Markov Linear Systems
Zakariya Laouar, Qi Heng Ho, Rayan Mazouz +2
In this paper, we present a controller framework that synthesizes control policies for Jump Markov Linear Systems subject to stochastic mode switches and imperfect mode estimation.…
Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
Rayan Mazouz, Karan Muvvala, Akash Ratheesh +2
Neural Networks (NNs) have been successfully employed to represent the state evolution of complex dynamical systems. Such models, referred to as NN dynamic models (NNDMs), use iter…