10 citations · 46 across the 28 of their papers we have counts for
5 papers · 1 filter
Reliable Probability Intervals For Classification Using Inductive Venn Predictors Based on Distance Learning
Dimitrios Boursinos, Xenofon Koutsoukos
Deep neural networks are frequently used by autonomous systems for their ability to learn complex, non-linear data patterns and make accurate predictions in dynamic environments. H…
Improving Prediction Confidence in Learning-Enabled Autonomous Systems
Dimitrios Boursinos, Xenofon Koutsoukos
Autonomous systems use extensively learning-enabled components such as deep neural networks (DNNs) for prediction and decision making. In this paper, we utilize a feedback loop bet…
Assurance Monitoring of Learning Enabled Cyber-Physical Systems Using Inductive Conformal Prediction based on Distance Learning
Dimitrios Boursinos, Xenofon Koutsoukos
Machine learning components such as deep neural networks are used extensively in Cyber-Physical Systems (CPS). However, such components may introduce new types of hazards that can…
Edge Augmentation with Controllability Constraints in Directed Laplacian Networks
Waseem Abbas, Mudassir Shabbir, Yasin Yazıcıoglu +1
In this paper, we study the maximum edge augmentation problem in directed Laplacian networks to improve their robustness while preserving lower bounds on their strong structural co…
Detection of Dataset Shifts in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression
Feiyang Cai, Ali I. Ozdagli, Xenofon Koutsoukos
Cyber-physical systems (CPSs) use learning-enabled components (LECs) extensively to cope with various complex tasks under high-uncertainty environments. However, the dataset shifts…