6 citations · 9 across the 4 of their papers we have counts for
4 papers
Detecting underdetermination in parameterized quantum circuits
Marie Kempkes, Jakob Spiegelberg, Evert van Nieuwenburg +1
A central question in machine learning is how reliable the predictions of a trained model are. Reliability includes the identification of instances for which a model is likely not…
Double descent in quantum kernel methods
Marie Kempkes, Aroosa Ijaz, Elies Gil-Fuster +4
The double descent phenomenon challenges traditional statistical learning theory by revealing scenarios where larger models do not necessarily lead to reduced performance on unseen…
Learning Density Functionals from Noisy Quantum Data
Emiel Koridon, Felix Frohnert, Eric Prehn +3
The search for useful applications of noisy intermediate-scale quantum (NISQ) devices in quantum simulation has been hindered by their intrinsic noise and the high costs associated…
Modern applications of machine learning in quantum sciences
Anna Dawid, Julian Arnold, Borja Requena +26
In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learn…