27 citations · 28 across the 6 of their papers we have counts for
6 papers
Toward Deployable Satellite Anomaly Detection: A Benchmark Study on Large-Scale ESA-ADB Telemetry
Andrea Nguyen, Dafne Rozenberg, Yeying Zhu +1
Satellite anomaly detection is essential for maintaining mission reliability and spacecraft health, yet remains challenging due to the high-dimensional, irregular, and imbalanced n…
HAPS-UAV-Enabled Heterogeneous Networks: A Deep Reinforcement Learning Approach
Atefeh H. Arani, Peng Hu, Yeying Zhu
The integrated use of non-terrestrial network (NTN) entities such as the high-altitude platform station (HAPS) and low-altitude platform station (LAPS) has become essential element…
Satellite Anomaly Detection Using Variance Based Genetic Ensemble of Neural Networks
Mohammad Amin Maleki Sadr, Yeying Zhu, Peng Hu
In this paper, we use a variance-based genetic ensemble (VGE) of Neural Networks (NNs) to detect anomalies in the satellite's historical data. We use an efficient ensemble of the p…
An Anomaly Detection Method for Satellites Using Monte Carlo Dropout
Mohammad Amin Maleki Sadr, Yeying Zhu, Peng Hu
Recently, there has been a significant amount of interest in satellite telemetry anomaly detection (AD) using neural networks (NN). For AD purposes, the current approaches focus on…
UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithms
Atefeh H. Arani, Peng Hu, Yeying Zhu
Recent technological advancements in space, air, and ground components have made possible a new network paradigm called space-air-ground integrated network (SAGIN). Unmanned aerial…
Matching Using Sufficient Dimension Reduction for Causal Inference
Wei Luo, Yeying Zhu
To estimate casual treatment effects, we propose a new matching approach based on the reduced covariates obtained from sufficient dimension reduction. Compared to the original cova…