| Prediction of functional ARMA processes with an application to traffic data J Klepsch, C Klüppelberg, T Wei Econometrics and Statistics 1, 128-149, 2017 | 106 | 2017 |
| Industry quantum computing applications A Bayerstadler, G Becquin, J Binder, T Botter, H Ehm, T Ehmer, ... EPJ Quantum Technology 8 (1), 25, 2021 | 101 | 2021 |
| An innovations algorithm for the prediction of functional linear processes J Klepsch, C Klüppelberg Journal of Multivariate Analysis 155, 252-271, 2017 | 51 | 2017 |
| Quantum computing: Towards industry reference problems A Luckow, J Klepsch, J Pichlmeier Digitale Welt 5, 38-45, 2021 | 39 | 2021 |
| Neutral atom quantum computing hardware: performance and end-user perspective K Wintersperger, F Dommert, T Ehmer, A Hoursanov, J Klepsch, ... EPJ Quantum Technology 10 (1), 32, 2023 | 30 | 2023 |
| Estimating functional time series by moving average model fitting A Aue, J Klepsch arXiv preprint arXiv:1701.00770, 2017 | 27 | 2017 |
| Quark: A framework for quantum computing application benchmarking JR Finžgar, P Ross, L Hölscher, J Klepsch, A Luckow 2022 IEEE international conference on quantum computing and engineering (QCE …, 2022 | 26 | 2022 |
| Optimization of robot-trajectory planning with nature-inspired and hybrid quantum algorithms MJA Schuetz, JK Brubaker, H Montagu, Y van Dijk, J Klepsch, P Ross, ... Physical Review Applied 18 (5), 054045, 2022 | 11 | 2022 |
| Quantum computing techniques for multi-knapsack problems A Awasthi, F Bär, J Doetsch, H Ehm, M Erdmann, M Hess, J Klepsch, ... Science and Information Conference, 264-284, 2023 | 10 | 2023 |
| Practical overview of image classification with tensor-network quantum circuits D Guala, S Zhang, E Cruz, CA Riofrío, J Klepsch, JM Arrazola Scientific Reports 13 (1), 4427, 2023 | 10 | 2023 |
| A serverless distributed ledger for enterprises J Sedlmeir, T Wagner, E Djerekarov, R Green, J Klepsch, S Rao arXiv preprint arXiv:2110.09221, 2021 | 10 | 2021 |
| Multivariate NoVaS and inference on conditional correlations D Thomakos, J Klepsch, D Politis Technical Report, 2016 | 10 | 2016 |
| A performance characterization of quantum generative models CA Riofrío, O Mitevski, C Jones, F Krellner, A Vučković, J Doetsch, ... arXiv preprint arXiv:2301.09363, 2023 | 6 | 2023 |
| Variable Selection for the Prediction of C [0, 1]-Valued Autoregressive Processes using Reproducing Kernel Hilbert Spaces B Bueno-Larraz, J Klepsch Technometrics, 2018 | 6 | 2018 |
| Quark: A framework for quantum computing application benchmarking (2022) JR Finzgar, P Ross, J Klepsch, A Luckow arXiv preprint arXiv:2202.03028, 0 | 5 | |
| Exploring privacy-enhancing technologies in the automotive value chain GM Garrido, K Schmidt, C Harth-Kitzerow, J Klepsch, A Luckow, F Matthes 2021 IEEE International Conference on Big Data (Big Data), 1265-1272, 2021 | 4 | 2021 |
| Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK FJ Kiwit, M Marso, P Ross, CA Riofrío, J Klepsch, A Luckow 2023 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2023 | 3 | 2023 |
| Challenges and Opportunities in Quantum Software Architecture T Yue, W Mauerer, S Ali, D Taibi Software Architecture: Research Roadmaps from the Community, 1-23, 2023 | 3 | 2023 |
| Model Free Inference on Multivariate Time Series with Conditional Correlations D Thomakos, J Klepsch, DN Politis Stats 3 (4), 484-509, 2020 | 3 | 2020 |
| Estimating invertible functional time series A Aue, J Klepsch Functional statistics and related fields, 51-58, 2017 | 3 | 2017 |
