4 papers · 1 filter
Quantum Gaussian processes for prediction of channel observations
Jonas Jäger, Yaroslav Khmelnitskiy, Paolo Braccia +4
Given a set of input states, we consider the task of predicting the expectation value of a Pauli observable at the output of an unknown quantum evolution, using only a limited numb…
Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation
Jonas Jäger, Florian J. Kiwit, Carlos A. Riofrío
Quantum generative modeling is a rapidly evolving discipline at the intersection of quantum computing and machine learning. Contemporary quantum machine learning is generally limit…
Quantum feature-map learning with reduced resource overhead
Jonas Jäger, Philipp Elsässer, Elham Torabian
Current quantum computers require algorithms that use limited resources economically. In quantum machine learning, success hinges on quantum feature-maps, which embed classical dat…
Equivalence between exponential concentration in quantum machine learning kernels and barren plateaus in variational algorithms
Pranav Kairon, Jonas Jäger, Roman V. Krems
We formalize a rigorous connection between barren plateaus (BP) in variational quantum algorithms and exponential concentration of quantum kernels for machine learning. Our results…