George Stamatelis

Orcid: 0000-0001-7826-2412

According to our database1, George Stamatelis authored at least 13 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Filtering Markov Jump Systems With Partially Known Dynamics: A Model-Based Deep Learning Approach.
IEEE Trans. Signal Process., 2026

Evolving Multi-Branch Attention Convolutional Neural Networks for Online RIS Configuration.
IEEE Trans. Cogn. Commun. Netw., 2026

Neural predictor aided policy optimization for adversarial controlled sensing.
Signal Process., 2026

2025
RIS-Enabled Smart Wireless Environments: Fundamentals and Distributed Optimization.
CoRR, December, 2025

Filtering Jump Markov Systems with Partially Known Dynamics: A Model-Based Deep Learning Approach.
CoRR, November, 2025

Joint Active RIS Configuration and User Power Control for Localization: A Neuroevolution-Based Approach.
CoRR, October, 2025

Evasive Active Hypothesis Testing With Deep Neuroevolution: The Single- and Multi-Agent Cases.
IEEE Trans. Inf. Forensics Secur., 2025

Learning RIS Configuration with Quantized Responses: A Neuroevolution-Trained Multi-Branch Attention Convolutional Neural Network.
Proceedings of the IEEE International Conference on Communications, 2025

On the Detection of Non-Cooperative RISs: Scan $B$-Testing via Deep Support Vector Data Description.
Proceedings of the IEEE International Conference on Communications, 2025

Multi-Agent Actor-Critic with Harmonic Annealing Pruning for Dynamic Spectrum Access Systems.
Proceedings of the 33rd European Signal Processing Conference, 2025

2024
Multi-Branch Attention Convolutional Neural Network for Online RIS Configuration with Discrete Responses: A Neuroevolution Approach.
CoRR, 2024

Single- and Multi-Agent Private Active Sensing: A Deep Neuroevolution Approach.
Proceedings of the IEEE International Conference on Communications Workshops, 2024

2023
Active Hypothesis Testing in Unknown Environments Using Recurrent Neural Networks and Model Free Reinforcement Learning.
Proceedings of the 31st European Signal Processing Conference, 2023


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