76 citations · 79 across the 10 of their papers we have counts for
13 papers
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…
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…
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…
Run Time Assurance for Safety-Critical Systems: An Introduction to Safety Filtering Approaches for Complex Control Systems
Kerianne Hobbs, Mark Mote, Matthew Abate +2
Run Time Assurance (RTA) Systems are online verification mechanisms that filter an unverified primary controller output to ensure system safety. The primary control may come from a…
A Numerical Method to Compute Stability Margins of Switching Linear Systems
Corbin Klett, Matthew Abate, Samuel Coogan +1
Stability margins for linear time-varying (LTV) and switched-linear systems are traditionally computed via quadratic Lyapunov functions, and these functions certify the stability o…
Improving the Fidelity of Mixed-Monotone Reachable Set Approximations via State Transformations
Matthew Abate, Samuel Coogan
Mixed-monotone systems are separable via a decomposition function into increasing and decreasing components, and this decomposition function allows for embedding the system dynamic…