7 citations · 10 across the 4 of their papers we have counts for
5 papers
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…
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…
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…