5 papers
Efficient training of photonic quantum generative models
Felix Gottlieb, Chayma Faraji, Rawad Mezher +3
The topic of generative learning has gained traction within the field of quantum machine learning, in particular with the advent of train-on-classical, deploy-on-quantum methods. T…
Quantum and classical processing with photonic quantum machine learning
J. C. López Carreño, S. Åwierczewski, A. Opala +3
Artificial intelligence and machine learning have been widely adopted both in the industry and in everyday life, but at the cost of high compute demands. Recent studies show that i…
MerLin: A Discovery Engine for Photonic and Hybrid Quantum Machine Learning
Cassandre Notton, Benjamin Stott, Philippe Schoeb +7
Identifying where quantum models may offer practical benefits in near term quantum machine learning (QML) requires moving beyond isolated algorithmic proposals toward systematic an…
Establishing Baselines for Photonic Quantum Machine Learning: Insights from an Open, Collaborative Initiative
Cassandre Notton, Vassilis Apostolou, Agathe Senellart +28
The Perceval Challenge is an open, reproducible benchmark designed to assess the potential of photonic quantum computing for machine learning. Focusing on a reduced and hardware-fe…
Error-mitigated photonic quantum circuit Born machine
Alexia Salavrakos, Tigran Sedrakyan, James Mills +2
In this article, we study quantum circuit Born machines (QCBMs) in the context of photonic quantum computing. QCBMs are a popular choice of quantum generative machine learning mode…