37 citations · 57 across the 8 of their papers we have counts for
9 papers
Data-Driven Modeling and Verification of Perception-Based Autonomous Systems
Thomas Waite, Alexander Robey, Hassani Hamed +2
This paper addresses the problem of data-driven modeling and verification of perception-based autonomous systems. We assume the perception model can be decomposed into a canonical…
Credal Bayesian Deep Learning
Michele Caprio, Souradeep Dutta, Kuk Jin Jang +4
Uncertainty quantification and robustness to distribution shifts are important goals in machine learning and artificial intelligence. Although Bayesian Neural Networks (BNNs) allow…
Risk Verification of Stochastic Systems with Neural Network Controllers
Matthew Cleaveland, Lars Lindemann, Radoslav Ivanov +1
Motivated by the fragility of neural network (NN) controllers in safety-critical applications, we present a data-driven framework for verifying the risk of stochastic dynamical sys…
A Framework for Checkpointing and Recovery of Hierarchical Cyber-Physical Systems
Kaustubh Sridhar, Radoslav Ivanov, Vuk Lesi +6
This paper tackles the problem of making complex resource-constrained cyber-physical systems (CPS) resilient to sensor anomalies. In particular, we present a framework for checkpoi…
Confidence Composition for Monitors of Verification Assumptions
Ivan Ruchkin, Matthew Cleaveland, Radoslav Ivanov +4
Closed-loop verification of cyber-physical systems with neural network controllers offers strong safety guarantees under certain assumptions. It is, however, difficult to determine…
ModelGuard: Runtime Validation of Lipschitz-continuous Models
Taylor J. Carpenter, Radoslav Ivanov, Insup Lee +1
This paper presents ModelGuard, a sampling-based approach to runtime model validation for Lipschitz-continuous models. Although techniques exist for the validation of many classes…
Confidence Calibration with Bounded Error Using Transformations
Sooyong Jang, Radoslav Ivanov, Insup Lee +1
As machine learning techniques become widely adopted in new domains, especially in safety-critical systems such as autonomous vehicles, it is crucial to provide accurate output unc…
Case Study: Verifying the Safety of an Autonomous Racing Car with a Neural Network Controller
Radoslav Ivanov, Taylor J. Carpenter, James Weimer +3
This paper describes a verification case study on an autonomous racing car with a neural network (NN) controller. Although several verification approaches have been proposed over t…
Verisig: verifying safety properties of hybrid systems with neural network controllers
Radoslav Ivanov, James Weimer, Rajeev Alur +2
This paper presents Verisig, a hybrid system approach to verifying safety properties of closed-loop systems using neural networks as controllers. Although techniques exist for veri…