5 papers
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…
Piquasso: A Photonic Quantum Computer Simulation Software Platform
Zoltán Kolarovszki, Tomasz Rybotycki, Péter Rakyta +10
We introduce the Piquasso quantum programming framework, a full-stack open-source software platform for the simulation and programming of photonic quantum computers. Piquasso can b…
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…
On the learning abilities of photonic continuous-variable Born machines
Zoltán Kolarovszki, Dániel T. R. Nagy, Zoltán Zimborás
This paper investigates photonic continuous-variable Born machines (CVBMs), which utilize photonic quantum states as resources for continuous probability distributions. Implementin…
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…