52 citations · 98 across the 37 of their papers we have counts for
45 papers
Data-Driven Compositional Safety Verification of Interconnected Monotone Systems
Amirreza Alavi, Majid Zamani, Saber Jafarpour
This paper introduces a sample-efficient compositional method for formal safety verification of interconnected monotone systems without requiring explicit models of the local subsy…
Reachability Analysis for Power Systems with Heterogeneous Resources via Jordan Transformation
Damola Ajeyemi, Antonin Colot, Sairaj Dhople +2
This paper develops a computationally efficient framework for reachability analysis of transmission-level power system dynamics with synchronous generators, grid-forming and grid-f…
Trajectory-based Safety of Monotone Systems: Verification and Control Synthesis
Felipe Galarza-Jimenez, Majid Zamani, Saber Jafarpour
This paper presents a novel data-driven framework for the robust safety verification and safe control synthesis of unknown monotone discrete-time systems. While existing data-drive…
Monotone Neural Barrier Certificates
Saber Jafarpour, Alireza Nadali, Ashutosh Trivedi +1
This report presents a neurosymbolic framework for safety verification and control synthesis in high-dimensional monotone dynamical systems without relying on explicit models or co…
Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
Damola Ajeyemi, Saber Jafarpour, Emiliano Dall'Anese
Control Barrier Functions (CBFs) have been widely utilized in the design of optimization-based controllers and filters for dynamical systems to ensure forward invariance of a given…
Safety Verification of Nonlinear Stochastic Systems via Probabilistic Tube
Zishun Liu, Saber Jafarpour, Yongxin Chen
We address the problem of safety verification for nonlinear stochastic systems, specifically the task of certifying that system trajectories remain within a safe set with high prob…
Geometric Reachability for Attitude Control Systems via Contraction Theory
Chencheng Xu, Saber Jafarpour, Chengcheng Zhao +2
In this paper, we present a geometric framework for the reachability analysis of attitude control systems. We model the attitude dynamics on the product manifold $\mathrm{SO}(3) \t…
Safety Verification of Stochastic Systems: A Set-Erosion Approach
Zishun Liu, Saber Jafarpour, Yongxin Chen
We study the safety verification problem for discrete-time stochastic systems. We propose an approach for safety verification termed set-erosion strategy that verifies the safety o…
Probabilistic Reachability of Discrete-Time Nonlinear Stochastic Systems
Zishun Liu, Saber Jafarpour, Yongxin Chen
In this paper we study the reachability problem for discrete-time nonlinear stochastic systems. Our goal is to present a unified framework for calculating the probabilistic reachab…
Probabilistic Reachability Analysis of Stochastic Control Systems
Saber Jafarpour, Zishun Liu, Yongxin Chen
We address the reachability problem for continuous-time stochastic dynamic systems. Our objective is to present a unified framework that characterizes the reachable set of a dynami…
: A Parallelizable and Differentiable Toolbox for Interval Analysis and Mixed Monotone Reachability in JAX
Akash Harapanahalli, Saber Jafarpour, Samuel Coogan
We present an implementation of interval analysis and mixed monotone interval reachability analysis as function transforms in Python, fully composable with the computational framew…
A Contracting Dynamical System Perspective toward Interval Markov Decision Processes
Saber Jafarpour, Samuel Coogan
Interval Markov decision processes are a class of Markov models where the transition probabilities between the states belong to intervals. In this paper, we study the problem of ef…
Forward Invariance in Neural Network Controlled Systems
Akash Harapanahalli, Saber Jafarpour, Samuel Coogan
We present a framework based on interval analysis and monotone systems theory to certify and search for forward invariant sets in nonlinear systems with neural network controllers.…
Efficient Interaction-Aware Interval Analysis of Neural Network Feedback Loops
Saber Jafarpour, Akash Harapanahalli, Samuel Coogan
In this paper, we propose a computationally efficient framework for interval reachability of systems with neural network controllers. Our approach leverages inclusion functions for…
A Toolbox for Fast Interval Arithmetic in numpy with an Application to Formal Verification of Neural Network Controlled Systems
Akash Harapanahalli, Saber Jafarpour, Samuel Coogan
In this paper, we present a toolbox for interval analysis in numpy, with an application to formal verification of neural network controlled systems. Using the notion of natural inc…
Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems
Akash Harapanahalli, Saber Jafarpour, Samuel Coogan
In this paper, we present a contraction-guided adaptive partitioning algorithm for improving interval-valued robust reachable set estimates in a nonlinear feedback loop with a neur…
Non-Euclidean Monotone Operator Theory and Applications
Alexander Davydov, Saber Jafarpour, Anton V. Proskurnikov +1
While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector space…
Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers
Saber Jafarpour, Akash Harapanahalli, Samuel Coogan
This paper proposes a computationally efficient framework, based on interval analysis, for rigorous verification of nonlinear continuous-time dynamical systems with neural network…
Monotonicity and Contraction on Polyhedral Cones
Saber Jafarpour, Samuel Coogan
In this note, we study monotone dynamical systems with respect to polyhedral cones. Using the half-space representation and the vertex representation, we propose three equivalent c…
Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach
Saber Jafarpour, Alexander Davydov, Matthew Abate +2
This paper proposes a theoretical and computational framework for training and robustness verification of implicit neural networks based upon non-Euclidean contraction theory. The…
Network Critical Slowing Down: Data-Driven Detection of Critical Transitions in Nonlinear Networks
Mohammad Pirani, Saber Jafarpour
In a Nature article, Scheffer et al. presented a novel data-driven framework to predict critical transitions in complex systems. These transitions, which may stem from failures, de…
Non-Euclidean Monotone Operator Theory with Applications to Recurrent Neural Networks
Alexander Davydov, Saber Jafarpour, Anton V. Proskurnikov +1
We provide a novel transcription of monotone operator theory to the non-Euclidean finite-dimensional spaces and . We first establish properties of mappings…
Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks
Alexander Davydov, Saber Jafarpour, Matthew Abate +2
We use interval reachability analysis to obtain robustness guarantees for implicit neural networks (INNs). INNs are a class of implicit learning models that use implicit equations…
Resilience of Input Metering in Dynamic Flow Networks
Saber Jafarpour, Samuel Coogan
In this paper, we study robustness of input metering policies in dynamic flow networks in the presence of transient disturbances and attacks. We consider a compartmental model for…