4 papers
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…
Qiboml: towards the orchestration of quantum-classical machine learning
Matteo Robbiati, Andrea Papaluca, Andrea Pasquale +12
We present Qiboml, an open-source software library for orchestrating quantum and classical components in hybrid machine learning workflows. Building on Qibo's quantum computing cap…
Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction
Alice Barthe, Mahtab Yaghubi Rad, Michele Grossi +1
One of the key challenges in quantum machine learning is finding relevant machine learning tasks with a provable quantum advantage. A natural candidate for this is learning unknown…
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…