13 citations · 18 across the 5 of their papers we have counts for
6 papers
Computing Headway Bounds under Worst-Case Bunching in Fixed-Line Transit Systems
Michael Yuhas, George Gunter, Jose Paulo Talusan +3
Vehicle bunching is a major problem for transit operators. When vehicles bunch together, the lead vehicle will service the majority of passenger demand, leaving the following vehic…
Co-Design of Out-of-Distribution Detectors for Autonomous Emergency Braking Systems
Michael Yuhas, Arvind Easwaran
Learning enabled components (LECs), while critical for decision making in autonomous vehicles (AVs), are likely to make incorrect decisions when presented with samples outside of t…
Demo Abstract: Real-Time Out-of-Distribution Detection on a Mobile Robot
Michael Yuhas, Arvind Easwaran
In a cyber-physical system such as an autonomous vehicle (AV), machine learning (ML) models can be used to navigate and identify objects that may interfere with the vehicle's opera…
Out of Distribution Reasoning by Weakly-Supervised Disentangled Logic Variational Autoencoder
Zahra Rahiminasab, Michael Yuhas, Arvind Easwaran
Out-of-distribution (OOD) detection, i.e., finding test samples derived from a different distribution than the training set, as well as reasoning about such samples (OOD reasoning)…
Design Methodology for Deep Out-of-Distribution Detectors in Real-Time Cyber-Physical Systems
Michael Yuhas, Daniel Jun Xian Ng, Arvind Easwaran
When machine learning (ML) models are supplied with data outside their training distribution, they are more likely to make inaccurate predictions; in a cyber-physical system (CPS),…
Embedded out-of-distribution detection on an autonomous robot platform
Michael Yuhas, Yeli Feng, Daniel Jun Xian Ng +2
Machine learning (ML) is actively finding its way into modern cyber-physical systems (CPS), many of which are safety-critical real-time systems. It is well known that ML outputs ar…