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quant-ph2025
Sample-based training of quantum generative models
Maria Demidik, Cenk Tüysüz, Michele Grossi +1
Quantum computers can efficiently sample from probability distributions that are believed to be classically intractable, providing a foundation for quantum generative modeling. How…
quant-ph2025
Expressive equivalence of classical and quantum restricted Boltzmann machines
Maria Demidik, Cenk Tüysüz, Nico Piatkowski +2
Quantum computers offer the potential for efficiently sampling from complex probability distributions, attracting increasing interest in generative modeling within quantum machine…
quant-ph2024
Learning to generate high-dimensional distributions with low-dimensional quantum Boltzmann machines
Cenk Tüysüz, Maria Demidik, Luuk Coopmans +5
In recent years, researchers have been exploring ways to generalize Boltzmann machines (BMs) to quantum systems, leading to the development of variations such as fully-visible and…