Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Johannes Klepsch"'
Autor:
Diego Guala, Shaoming Zhang, Esther Cruz, Carlos A. Riofrío, Johannes Klepsch, Juan Miguel Arrazola
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Circuit design for quantum machine learning remains a formidable challenge. Inspired by the applications of tensor networks across different fields and their novel presence in the classical machine learning context, one proposed method to de
Externí odkaz:
https://doaj.org/article/2af4fcd13b834f99b56afbfaf4608ef7
Publikováno v:
Stats, Vol 3, Iss 4, Pp 484-509 (2020)
New results on volatility modeling and forecasting are presented based on the NoVaS transformation approach. Our main contribution is that we extend the NoVaS methodology to modeling and forecasting conditional correlation, thus allowing NoVaS to wor
Externí odkaz:
https://doaj.org/article/72a31c00e9834eb5a06a8ae72798df73
Autor:
Martin J.A. Schuetz, J. Kyle Brubaker, Henry Montagu, Yannick van Dijk, Johannes Klepsch, Philipp Ross, Andre Luckow, Mauricio G.C. Resende, Helmut G. Katzgraber
We solve robot trajectory planning problems at industry-relevant scales. Our end-to-end solution integrates highly versatile random-key algorithms with model stacking and ensemble techniques, as well as path relinking for solution refinement. The cor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3002c131cc431525c949cc987a79634c
http://arxiv.org/abs/2206.03651
http://arxiv.org/abs/2206.03651
Enterprises have been attracted by the capability of blockchains to provide a single source of truth for workloads that span companies, geographies, and clouds while retaining the independence of each party's IT operations. However, so far production
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1844940f1d77aff1b2ec5713e4dedac
http://orbilu.uni.lu/handle/10993/53790
http://orbilu.uni.lu/handle/10993/53790
Autor:
Gonzalo Munilla Garrido, Kaja Schmidt, Christopher Harth-Kitzerow, Johannes Klepsch, Andre Luckow, Florian Matthes
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Privacy-enhancing technologies (PETs) are becoming increasingly crucial for addressing customer needs, security, privacy (e.g., enhancing anonymity and confidentiality), and regulatory requirements. However, applying PETs in organizations requires a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43d5a623c2b927877a8ced563ba6ac42
https://doi.org/10.1109/bigdata52589.2021.9671528
https://doi.org/10.1109/bigdata52589.2021.9671528
Autor:
Hans Ehm, Clemens Utschig-Utschig, Norbert Gaus, Michael Streif, Christoph Niedermeier, Florian Neukart, Maximilian Hess, Thomas Ehmer, Tammo Sievers, Marvin Erdmann, Thierry Botter, Guillaume Becquin, Maximilian Mansky, Julia Binder, Fabian Winter, Lilly Palackal, Johannes Klepsch, Daniel Volz, Horst Weiss, Andreas Bayerstadler, Thomas Strohm, Wolfgang Mauerer, Brian Standen, Sebastian Luber, Carsten Polenz, Philipp Harbach, Ruben Pfeiffer, Martin Leib, Johanna Sepulveda, Andre Luckow
Publikováno v:
EPJ Quantum Technology. 8
Quantum computing promises to overcome computational limitations with better and faster solutions for optimization, simulation, and machine learning problems. Europe and Germany are in the process of successfully establishing research and funding pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb7d46ae0240338c3516915a39105e82
https://doi.org/10.1140/epjqt/s40507-021-00114-x
https://doi.org/10.1140/epjqt/s40507-021-00114-x
The complexity is increasing rapidly in many areas of the automotive industry. The design of an automobile involves many different engineering disciplines, e. g., mechanical, electrical, and software engineering. The software of a vehicle comprises m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3fe472f82f6a1a5f40f8db31d22ac8d0
http://arxiv.org/abs/2103.07433
http://arxiv.org/abs/2103.07433
Autor:
Johannes Klepsch, Beatriz Bueno-Larraz
Publikováno v:
Technometrics. 61:139-153
A model for the prediction of functional time series is introduced, where observations are assumed to be continuous random functions. We model the dependence of the data with a nonstandard autoregr...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b67e69111d278061f854c6e21b52b0d
https://doi.org/10.1080/00401706.2018.1505660
https://doi.org/10.1080/00401706.2018.1505660
Autor:
Alexander Aue, Johannes Klepsch
Publikováno v:
Contributions to Statistics ISBN: 9783319558455
This contribution discusses the estimation of an invertible functional time series through fitting of functional moving average processes. The method uses a functional version of the innovations algorithm and dimension reduction onto a number of prin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::095b46bf2db53a136d97d41082a5e2af
https://doi.org/10.1007/978-3-319-55846-2_8
https://doi.org/10.1007/978-3-319-55846-2_8