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06/09/2023
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
Machine learning provides a valuable tool for analyzing high-dimensional...
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06/06/2023
Learning-Based Heuristic for Combinatorial Optimization of the Minimum Dominating Set Problem using Graph Convolutional Networks
A dominating set of a graph 𝒢=(𝒱, ℰ) is a subset of vertices S⊆𝒱 such th...
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05/23/2023
Sequential Graph Neural Networks for Source Code Vulnerability Identification
Vulnerability identification constitutes a task of high importance for c...
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06/11/2022
Web-Based Platform for Evaluation of Resilient and Transactive Smart-Grids
Today's smart-grids have seen a clear rise in new ways of energy generat...
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03/16/2022
Open Set Recognition using Vision Transformer with an Additional Detection Head
Deep neural networks have demonstrated prominent capacities for image cl...
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10/07/2021
Reliable Probability Intervals For Classification Using Inductive Venn Predictors Based on Distance Learning
Deep neural networks are frequently used by autonomous systems for their...
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10/07/2021
Improving Prediction Confidence in Learning-Enabled Autonomous Systems
Autonomous systems use extensively learning-enabled components such as d...
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10/07/2021
Assurance Monitoring of Learning Enabled Cyber-Physical Systems Using Inductive Conformal Prediction based on Distance Learning
Machine learning components such as deep neural networks are used extens...
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05/13/2021
Edge Augmentation with Controllability Constraints in Directed Laplacian Networks
In this paper, we study the maximum edge augmentation problem in directe...
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04/14/2021
Detection of Dataset Shifts in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression
Cyber-physical systems (CPSs) use learning-enabled components (LECs) ext...
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10/25/2020
Byzantine Resilient Distributed Multi-Task Learning
Distributed multi-task learning provides significant advantages in multi...
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03/23/2020
Resilient Distributed Diffusion for Multi-task Estimation
Distributed diffusion is a powerful algorithm for multi-task state estim...
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03/23/2020
Resilient Distributed Diffusion in Networks with Adversaries
In this paper, we study resilient distributed diffusion for multi-task e...
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03/21/2020
Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression
Learning-enabled components (LECs) are widely used in cyber-physical sys...
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03/11/2020
Trusted Confidence Bounds for Learning Enabled Cyber-Physical Systems
Cyber-physical systems (CPS) can benefit by the use of learning enabled ...
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01/28/2020
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems
Cyber-physical systems (CPS) greatly benefit by using machine learning c...
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01/14/2020
Assurance Monitoring of Cyber-Physical Systems with Machine Learning Components
Machine learning components such as deep neural networks are used extens...
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08/28/2018
Synergistic Security for the Industrial Internet of Things: Integrating Redundancy, Diversity, and Hardening
As the Industrial Internet of Things (IIot) becomes more prevalent in cr...
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08/25/2018
Detection and Mitigation of Attacks on Transportation Networks as a Multi-Stage Security Game
In recent years, state-of-the-art traffic-control devices have evolved f...
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04/30/2018
Adversarial Regression for Detecting Attacks in Cyber-Physical Systems
Attacks in cyber-physical systems (CPS) which manipulate sensor readings...
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02/08/2017