1 citations · 1 across the 4 of their papers we have counts for
6 papers
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…
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…
Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach
Saber Jafarpour, Matthew Abate, Alexander Davydov +2
Implicit neural networks are a general class of learning models that replace the layers in traditional feedforward models with implicit algebraic equations. Compared to traditional…