51 citations · 118 across the 22 of their papers we have counts for
24 papers
Targeted collapse regularized autoencoder for anomaly detection: black hole at the center
Amin Ghafourian, Huanyi Shui, Devesh Upadhyay +3
Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the a…
KARNet: Kalman Filter Augmented Recurrent Neural Network for Learning World Models in Autonomous Driving Tasks
Hemanth Manjunatha, Andrey Pak, Dimitar Filev +1
Autonomous driving has received a great deal of attention in the automotive industry and is often seen as the future of transportation. The development of autonomous driving techno…
Experience-Based Evolutionary Algorithms for Expensive Optimization
Xunzhao Yu, Yan Wang, Ling Zhu +2
Optimization algorithms are very different from human optimizers. A human being would gain more experiences through problem-solving, which helps her/him in solving a new unseen pro…
Safe Control and Learning Using Generalized Action Governor
Peiyuan Fang, Weiqi Zhang, Lu Xiong +7
This paper introduces the Generalized Action Governor (AG), a supervisory scheme that augments a nominal closed-loop system with the capability to enforce state and input constrain…
Safe and Human-Like Autonomous Driving: A Predictor-Corrector Potential Game Approach
Mushuang Liu, H. Eric Tseng, Dimitar Filev +2
This paper proposes a novel decision-making framework for autonomous vehicles (AVs), called predictor-corrector potential game (PCPG), composed of a Predictor and a Corrector. To e…
Robust Action Governor for Uncertain Piecewise Affine Systems with Non-convex Constraints and Safe Reinforcement Learning
Yutong Li, Nan Li, H. Eric Tseng +3
The action governor is an add-on scheme to a nominal control loop that monitors and adjusts the control actions to enforce safety specifications expressed as pointwise-in-time stat…