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Sebastian Schmitt
Sebastian Schmitt
Honda Research Institute Europe GmbH
Geverifieerd e-mailadres voor honda-ri.de
Titel
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Jaar
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
3172022
Recent Advances in Bayesian Optimization
X Wang, Y Jin, S Schmitt, M Olhofer
ACM Computing Surveys, 2023
2932023
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
1542020
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
1521999
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
1332020
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—Condensed Matter and Materials Physics 81 (16), 165106, 2010
422010
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
412023
study of Ru-based perovskite and
E Jakobi, S Kanungo, S Sarkar, S Schmitt, T Saha-Dasgupta
Physical Review B—Condensed Matter and Materials Physics 83 (4), 041103, 2011
402011
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
352021
Non-Fermi-liquid signatures in the Hubbard model due to van Hove singularities
S Schmitt
Physical Review B—Condensed Matter and Materials Physics 82 (15), 155126, 2010
352010
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
352008
Nonequilibrium Zeeman splitting in quantum transport through nanoscale junctions
S Schmitt, FB Anders
Physical review letters 107 (5), 056801, 2011
312011
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
292023
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
292020
Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise
A Castellani, S Schmitt, B Hammer
Machine Learning and Knowledge Discovery in Databases. Research Track. (ECML …, 2021
262021
Spectral properties of the two-impurity Anderson model with varying distance and various interactions
T Jabben, N Grewe, S Schmitt
Physical Review B—Condensed Matter and Materials Physics 85 (4), 045133, 2012
262012
Task-Sensitive Concept Drift Detector with Constraint Embedding
A Castellani, S Schmitt, B Hammer
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-08, 2021
232021
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
222022
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—Condensed Matter and Materials Physics 84 (20), 205104, 2011
212011
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
192019
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Artikelen 1–20