1 citations · 1 across the 2 of their papers we have counts for
4 papers
Noise-Assisted Variational Quantum Thermalization
Jonathan Foldager, Arthur Pesah, Lars Kai Hansen
Preparing thermal states on a quantum computer can have a variety of applications, from simulating many-body quantum systems to training machine learning models. Variational circui…
Absence of Barren Plateaus in Quantum Convolutional Neural Networks
Arthur Pesah, M. Cerezo, Samson Wang +3
Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by the existence of exp…
Quantum Machine Learning in High Energy Physics
Wen Guan, Gabriel Perdue, Arthur Pesah +4
Machine learning has been used in high energy physics for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early…
Recurrent machines for likelihood-free inference
Arthur Pesah, Antoine Wehenkel, Gilles Louppe
Likelihood-free inference is concerned with the estimation of the parameters of a non-differentiable stochastic simulator that best reproduce real observations. In the absence of a…