Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Jonas M Kübler"'
Autor:
Jonas M Kübler, Daniel Braun
Publikováno v:
New Journal of Physics, Vol 20, Iss 8, p 083015 (2018)
We study quantum causal inference in a setup proposed by Ried et al (2015 Nat. Phys. 11 414) in which a common cause scenario can be mixed with a cause–effect scenario, and for which it was found that quantum mechanics can bring an advantage in dis
Externí odkaz:
https://doaj.org/article/5c73df0eb9be4d55961e7d366eea48cc
Publikováno v:
Quantum, Vol 4, p 263 (2020)
Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regarding the number of measurements needed for convergence of VHQCAs. Here,
Externí odkaz:
https://doaj.org/article/6e1ce685633b4a8a9fdaed85766ac316
Publikováno v:
Physical Review Research, Vol 1, Iss 3, p 033159 (2019)
The kernel mean embedding of probability distributions is commonly used in machine learning as an injective mapping from distributions to functions in an infinite-dimensional Hilbert space. It allows us, for example, to define a distance measure betw
Externí odkaz:
https://doaj.org/article/2e2f883598bc4160963daa327e9a7c68
Autor:
Sofiene Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, Vedran Dunjko
Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and studied extens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eea6504a2f075a3edceed627722b94a8
Autor:
Lukas Zimmermann, Jonas M. Kübler, Marko Lozajic, Andrei N. Lupas, Felix Gabler, David Rau, Johannes Söding, Seung-Zin Nam, Vikram Alva, Andrew Stephens
Publikováno v:
Journal of Molecular Biology. 430:2237-2243
The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) is a free, one-stop web service for protein bioinformatic analysis. It currently offers 34 interconnected external and in-house tools, whose functionality covers sequence similarity se
Autor:
Sofiene Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, Vedran Dunjko
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-8 (2023)
Comparing the capabilities of different quantum machine learning protocols is difficult. Here, the authors show that different learning models based on parametrized quantum circuits can all be seen as quantum linear models, thus driving general concl
Externí odkaz:
https://doaj.org/article/be9a37f1040943988bb2f3b9570a8b1a