3 citations · 3 across the 3 of their papers we have counts for
9 papers
Towards interpretable AI with quantum annealing feature selection
Francesco Aldo Venturelli, Emanuele Costa, Sikha O K +3
Deep learning models are used in critical applications, in which mistakes can have serious consequences. Therefore, it is crucial to understand how and why models generate predicti…
Gauge and diffeomorphism invariance from quantum information principles
Claudia Núñez, Miguel Pardina, Manuel Asorey +2
Entanglement is a hallmark of quantum theory, yet it alone does not capture the full extent of quantum complexity: some highly entangled states can still be classically simulated.…
Universality of entanglement in gluon dynamics
Claudia Núñez, Alba Cervera-Lierta, José Ignacio Latorre
Entanglement of fundamental degrees of freedom in particle physics is generated ab initio in scattering processes. In the case of a pure gauge theory, two gluons in a produ…
Warm Starts, Cold States: Exploiting Adiabaticity for Variational Ground-States
Ricard Puig, Berta Casas, Alba Cervera-Lierta +2
Reliable preparation of many-body ground states is an essential task in quantum computing, with applications spanning areas from chemistry and materials modeling to quantum optimiz…
Hardware-inspired Continuous Variables Quantum Optical Neural Networks
Todor Krasimirov-Ivanov, Alba Cervera-Lierta, Paolo Stornati +1
Continuous-variables (CV) quantum optics is a natural formalism for neural networks (NNs) due to its ability to reproduce the information processing of such trainable interconnecte…
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…