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
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…
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…