193 citations · 759 across the 35 of their papers we have counts for
8 papers · 2 filters
Financial Risk Management on a Neutral Atom Quantum Processor
Lucas Leclerc, Luis Ortiz-Guitierrez, Sebastian Grijalva +19
Machine Learning models capable of handling the large datasets collected in the financial world can often become black boxes expensive to run. The quantum computing paradigm sugges…
Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Boris Albrecht, Constantin Dalyac, Lucas Leclerc +10
Using a quantum processor to embed and process classical data enables the generation of correlations between variables that are inefficient to represent through classical computati…
Purification-based quantum error mitigation of pair-correlated electron simulations
T. E. O'Brien, G. Anselmetti, F. Gkritsis +173
An important measure of the development of quantum computing platforms has been the simulation of increasingly complex physical systems. Prior to fault-tolerant quantum computing,…
Protocols for classically training quantum generative models on probability distributions
Sachin Kasture, Oleksandr Kyriienko, Vincent E. Elfving
Quantum Generative Modelling (QGM) relies on preparing quantum states and generating samples from these states as hidden - or known - probability distributions. As distributions fr…
Integral Transforms in a Physics-Informed (Quantum) Neural Network setting: Applications & Use-Cases
Niraj Kumar, Evan Philip, Vincent E. Elfving
In many computational problems in engineering and science, function or model differentiation is essential, but also integration is needed. An important class of computational probl…
Quantum Extremal Learning
Savvas Varsamopoulos, Evan Philip, Herman W. T. van Vlijmen +6
We propose a quantum algorithm for `extremal learning', which is the process of finding the input to a hidden function that extremizes the function output, without having direct ac…