Real photon scattering up to 10 MeV: the improved facility at the Darmstadt electron accelerator S-DALINAC P Mohr, J Enders, T Hartmann, H Kaiser, D Schiesser, S Schmitt, S Volz, ...
Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 1999
155 1999 Quantum Annealing for Industry Applications: Introduction and Review S Yarkoni, E Raponi, T Bäck, S Schmitt
Reports on Progress in Physics 85 (10), 104001, 2022
101 2022 An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization X Wang, Y Jin, S Schmitt, M Olhofer
Information Sciences 519, 317-331, 2020
79 2020 Real-World Anomaly Detection by Using Digital Twin Systems and Weakly Supervised Learning A Castellani, S Schmitt, S Squartini
IEEE Transactions on Industrial Informatics 17 (7), 4733-4742, 2020
72 2020 Learning fluid flows T Georgiou, S Schmitt, M Olhofer, Y Liu, T Bäck, M Lew
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
47 2018 Comparison between scattering-states numerical renormalization group and the Kadanoff-Baym-Keldysh approach to quantum transport: Crossover from weak to strong correlations S Schmitt, FB Anders
Physical Review B 81 (16), 165106, 2010
42 2010 E Jakobi, S Kanungo, S Sarkar, S Schmitt, T Saha-Dasgupta
Physical Review B 83 (4), 041103, 2011
38 2011 Conserving approximations in direct perturbation theory: new semianalytical impurity solvers and their application to general lattice problems N Grewe, S Schmitt, T Jabben, FB Anders
Journal of Physics: Condensed Matter 20 (36), 365217, 2008
35 2008 Nonequilibrium Zeeman splitting in quantum transport through nanoscale junctions S Schmitt, FB Anders
Physical review letters 107 (5), 056801, 2011
31 2011 Non-Fermi-liquid signatures in the Hubbard model due to van Hove singularities S Schmitt
Physical Review B 82 (15), 155126, 2010
27 2010 Transfer learning for gaussian process assisted evolutionary bi-objective optimization for objectives with different evaluation times X Wang, Y Jin, S Schmitt, M Olhofer
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 587-594, 2020
24 2020 Transfer learning based surrogate assisted evolutionary bi-objective optimization for objectives with different evaluation times X Wang, Y Jin, S Schmitt, M Olhofer, R Allmendinger
Knowledge-Based Systems 227, 107190, 2021
23 2021 Recent Advances in Bayesian Optimization X Wang, Y Jin, S Schmitt, M Olhofer
ACM Computing Surveys, 2023
22 2023 Spectral properties of the two-impurity Anderson model with varying distance and various interactions T Jabben, N Grewe, S Schmitt
Physical Review B 85 (4), 045133, 2012
21 2012 Kinks in the electronic dispersion of the Hubbard model away from half filling P Grete, S Schmitt, C Raas, FB Anders, GS Uhrig
Physical Review B 84 (20), 205104, 2011
21 2011 Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. S Däubener, S Schmitt, H Wang, P Krause, T Bäck
ICDM, 161-175, 2019
19 2019 Dynamic susceptibilities of the single-impurity Anderson model within an enhanced noncrossing approximation S Schmitt, T Jabben, N Grewe
Physical Review B 80 (23), 235130, 2009
17 2009 Quantum approximate optimization algorithm for qudit systems Y Deller, S Schmitt, M Lewenstein, S Lenk, F Federer , M, Jendrzejewski, ...
Phys. Rev. A 107, 062410, 2023
15 2023 A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition P Wollstadt, S Schmitt, M Wibral
Journal of Machine Learning Research 24 (131), 1--44, 2023
15 2023 Transfer Learning Based Co-Surrogate Assisted Evolutionary Bi-Objective Optimization for Objectives with Non-Uniform Evaluation Times X Wang, Y Jin, S Schmitt, M Olhofer
Evolutionary computation 30 (2), 221-251, 2022
15 2022 
OlhoferHonda Research Institute EuropeEmail verificata su honda-ri.de
