3 papers
cs.LG2026
Multitask Learning for Earth Observation Data Classification with Hybrid Quantum Network
Fan Fan, Yilei Shi, Tobias Guggemos +1
Quantum machine learning (QML) has gained increasing attention as a potential solution to address the challenges of computation requirements in the future. Earth observation (EO) h…
quant-ph2026
Adaptive Framework for Failure-Aware Protocols in Fusion-Based Graph-State Generation
Korbinian Staudacher, Bhilahari Jeevanesan, Tobias Guggemos
We consider the generation of photonic graph states in a linear optics setting where sequential non-deterministic fusion measurements are used to build large graph states out of sm…
physics.ed-ph2024
Training Computer Scientists for the Challenges of Hybrid Quantum-Classical Computing
Vincenzo De Maio, Meerzhan Kanatbekova, Felix Zilk +3
As we enter the post-Moore era, we experience the rise of various non-von-Neumann-architectures to address the increasing computational demand for modern applications, with quantum…