Quantum Reupload Units: A Scalable and Expressive Approach for Time Series Learning
Oral conference presentation IEEE International Conference on Quantum Computing and Engineering (QCE25) Montréal, Canada
Presentation of a single-qubit Quantum Reupload Unit for time-series learning, including spectral expressivity, trainability, and real-data forecasting.
I presented the QRU time-series work at IEEE Quantum Week 2025. The talk covered compact circuit design, repeated data encoding, spectral interpretation, controlled comparisons with classical and quantum baselines, and practical execution constraints.