49 citations · 83 across the 6 of their papers we have counts for
11 papers
Hybrid Quantum-Classical Reinforcement Learning in Latent Observation Spaces
Dániel T. R. Nagy, Csaba Czabán, Bence Bakó +3
Recent progress in quantum machine learning has sparked interest in using quantum methods to tackle classical control problems via quantum reinforcement learning. However, the clas…
Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication
Zsolt I. Tabi, Bence Bakó, Dániel T. R. Nagy +4
This paper presents a comprehensive study on the possible hybrid quantum-classical autoencoder architectures for end-to-end radio communication against noisy channel conditions usi…
Problem-informed Graphical Quantum Generative Learning
Bence Bakó, Dániel T. R. Nagy, Péter Hága +2
Leveraging the intrinsic probabilistic nature of quantum systems, generative quantum machine learning (QML) offers the potential to outperform classical learning models. Current ge…
Hybrid Quantum-Classical Autoencoders for End-to-End Radio Communication
Zsolt Tabi, Bence Bakó, Dániel T. R. Nagy +4
Quantum neural networks are emerging as potential candidates to leverage noisy quantum processing units for applications. Here we introduce hybrid quantum-classical autoencoders fo…
Photonic Quantum Policy Learning in OpenAI Gym
Dániel Nagy, Zsolt Tabi, Péter Hága +2
In recent years, near-term noisy intermediate scale quantum (NISQ) computing devices have become available. One of the most promising application areas to leverage such NISQ quantu…
Quantum Optimization for the Graph Coloring Problem with Space-Efficient Embedding
Zsolt Tabi, Kareem H. El-Safty, Zsófia Kallus +4
Current quantum computing devices have different strengths and weaknesses depending on their architectures. This means that flexible approaches to circuit design are necessary. We…