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quant-ph2025★ 2 cited
Quantum generative modeling for financial time series with temporal correlations
David Dechant, Eliot Schwander, Lucas van Drooge +4
Quantum generative adversarial networks (QGANs) have been investigated as a method for generating synthetic data with the goal of augmenting training data sets for neural networks.…
quant-ph2025
Evaluation of derivatives using approximate generalized parameter shift rule
Vytautas Abramavicius, Evan Philip, Kaonan Micadei +5
Parameter shift rules are instrumental for derivatives estimation in a wide range of quantum algorithms, especially in the context of Quantum Machine Learning. Application of singl…