5 citations · 8 across the 3 of their papers we have counts for
3 papers
quant-ph2026
Learning ground state observables from quantum computing experiments
Ben Jaderberg, Freya Shah, Minjun Jeon +3
Recent theoretical progress has established conditions under which machine learning models can efficiently predict ground-state properties of gapped local Hamiltonians when trained…
quant-ph2024★ 3 cited
Dynamic parameterized quantum circuits: expressive and barren-plateau free
Abhinav Deshpande, Marcel Hinsche, Khadijeh Najafi +3
Classical optimization of parameterized quantum circuits is a widely studied methodology for the preparation of complex quantum states, as well as the solution of machine learning…
quant-ph2022★ 5 cited
On Quantum Circuits for Discrete Graphical Models
Nico Piatkowski, Christa Zoufal
Graphical models are useful tools for describing structured high-dimensional probability distributions. Development of efficient algorithms for generating unbiased and independent…