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cs.LG2026
Towards interpretable AI with quantum annealing feature selection
Francesco Aldo Venturelli, Emanuele Costa, Sikha O K +3
Deep learning models are used in critical applications, in which mistakes can have serious consequences. Therefore, it is crucial to understand how and why models generate predicti…
cs.LG2021★ 25 cited
Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models
Daniel Flam-Shepherd, Tony Wu, Xuemei Gu +3
Quantum physics experiments produce interesting phenomena such as interference or entanglement, which are core properties of numerous future quantum technologies. The complex relat…