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most citedPerformance Analysis of Machine Learning Centered Workload Prediction Models for Cloud

128 citations

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quant-ph2023★ 8 cited

Good Gottesman-Kitaev-Preskill codes from the NTRU cryptosystem

Jonathan Conrad, Jens Eisert, Jean-Pierre Seifert

We introduce a new class of random Gottesman-Kitaev-Preskill (GKP) codes derived from the cryptanalysis of the so-called NTRU cryptosystem. The derived codes are good in that they…

quant-ph2022★ 18 cited

A super-polynomial quantum-classical separation for density modelling

Niklas Pirnay, Ryan Sweke, Jens Eisert +1

Density modelling is the task of learning an unknown probability density function from samples, and is one of the central problems of unsupervised machine learning. In this work, w…

quant-ph2021★ 13 cited

Learning Classical Readout Quantum PUFs based on single-qubit gates

Niklas Pirnay, Anna Pappa, Jean-Pierre Seifert

Physical Unclonable Functions (PUFs) have been proposed as a way to identify and authenticate electronic devices. Recently, several ideas have been presented that aim to achieve th…

quant-ph2020★ 85 cited

On the Quantum versus Classical Learnability of Discrete Distributions

Ryan Sweke, Jean-Pierre Seifert, Dominik Hangleiter +1

Here we study the comparative power of classical and quantum learners for generative modelling within the Probably Approximately Correct (PAC) framework. More specifically we consi…