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20222026
most citedBenchmarking Quantum Reinforcement Learning

3 citations · 7 across the 12 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.LG2025

Meta-Learning Multi-armed Bandits for Beam Tracking in 5G and 6G Networks

Alexander Mattick, George Yammine, Georgios Kontes +2

Beamforming-capable antenna arrays with many elements enable higher data rates in next generation 5G and 6G networks. In current practice, analog beamforming uses a codebook of pre…

eess.SP2025

Hardware Limitations and Optimization Approach in 1-Bit RIS Design at 28 GHz

Hossein Rezaei, Mehmet Emin Arslan, George Yammine +2

Reconfigurable intelligent surfaces (RIS) have emerged as a transformative technology for electromagnetic (EM) wave manipulation, offering unprecedented control over wave reflectio…

eess.SP2025

Passive Channel Charting: Locating Passive Targets using a UWB Mesh

Raffael Poeggel, Maximilian Stahlke, Jonas Pirkl +4

Fingerprint-based passive localization enables high localization accuracy using low-cost UWB IoT radio sensors. However, fingerprinting demands extensive effort for data acquisitio…

quant-ph2025★ 3 cited

Benchmarking Quantum Reinforcement Learning

Georg Kruse, Rodrigo Coelho, Andreas Rosskopf +2

Quantum Reinforcement Learning (QRL) has emerged as a promising research field, leveraging the principles of quantum mechanics to enhance the performance of reinforcement learning…

quant-ph2025★ 1 cited

Benchmarking Quantum Reinforcement Learning

Nico Meyer, Christian Ufrecht, George Yammine +3

Benchmarking and establishing proper statistical validation metrics for reinforcement learning (RL) remain ongoing challenges, where no consensus has been established yet. The emer…