50 citations · 83 across the 3 of their papers we have counts for
5 papers
Cost function embedding and dataset encoding for machine learning with parameterized quantum circuits
Shuxiang Cao, Leonard Wossnig, Brian Vlastakis +2
Machine learning is seen as a promising application of quantum computation. For near-term noisy intermediate-scale quantum (NISQ) devices, parametrized quantum circuits (PQCs) have…
Dynamical mean field theory algorithm and experiment on quantum computers
I. Rungger, N. Fitzpatrick, H. Chen +12
The developments of quantum computing algorithms and experiments for atomic scale simulations have largely focused on quantum chemistry for molecules, while their application in co…
Generative training of quantum Boltzmann machines with hidden units
Nathan Wiebe, Leonard Wossnig
In this article we provide a method for fully quantum generative training of quantum Boltzmann machines with both visible and hidden units while using quantum relative entropy as a…
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
Edward Grant, Leonard Wossnig, Mateusz Ostaszewski +1
Parametrized quantum circuits initialized with random initial parameter values are characterized by barren plateaus where the gradient becomes exponentially small in the number of…
Quantum-classical truncated Newton method for high-dimensional energy landscapes
Leonard Wossnig, Sebastian Tschiatschek, Stefan Zohren
We develop a quantum-classical hybrid algorithm for function optimization that is particularly useful in the training of neural networks since it makes use of particular aspects of…