activity
20202022
most citedReal-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems

10 citations · 10 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Open Set Recognition using Vision Transformer with an Additional Detection Head

Feiyang Cai, Zhenkai Zhang, Jie Liu +1

Deep neural networks have demonstrated prominent capacities for image classification tasks in a closed set setting, where the test data come from the same distribution as the train…

cs.LG2021

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…

cs.CV2020

Association: Remind Your GAN not to Forget

Yi Gu, Jie Li, Yuting Gao +5

Neural networks are susceptible to catastrophic forgetting. They fail to preserve previously acquired knowledge when adapting to new tasks. Inspired by human associative memory sys…

cs.LG2020

Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression

Feiyang Cai, Jiani Li, Xenofon Koutsoukos

Learning-enabled components (LECs) are widely used in cyber-physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level o…

cs.LG202010 cited

Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems

Feiyang Cai, Xenofon Koutsoukos

Cyber-physical systems (CPS) greatly benefit by using machine learning components that can handle the uncertainty and variability of the real-world. Typical components such as deep…