3 papers
quant-ph2026
Encoding Numerical Data for Generative Quantum Machine Learning
Michael Krebsbach, Florentin Reiter, Thomas Wellens +2
Generative quantum machine learning models are trained to deduce the probability distribution underlying a given dataset, and to produce new, synthetic samples from it. The majorit…
cs.LG2025
Synthetic Data Generation and Differential Privacy using Tensor Networks' Matrix Product States (MPS)
Alejandro Moreno R., Desale Fentaw, Samuel Palmer +7
Synthetic data generation is a key technique in modern artificial intelligence, addressing data scarcity, privacy constraints, and the need for diverse datasets in training robust…
cs.LG2025
Blockchain Network Analysis using Quantum Inspired Graph Neural Networks & Ensemble Models
Luigi D'Amico, Daniel De Rosso, Ninad Dixit +6
In the rapidly evolving domain of financial technology, the detection of illicit transactions within blockchain networks remains a critical challenge, necessitating robust and inno…