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2020 – today
- 2023
[j2]Ahmad Idrissi-Yaghir
, Henning Schäfer, Nadja Bauer, Christoph M. Friedrich:
Domain Adaptation of Transformer-Based Models Using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback. SN Comput. Sci. 4(2): 142 (2023)- 2022
- [c4]Alexander Schulte, Tim Breiksch, Jonas Brockmann, Nadja Bauer:
Machine Learning Based Classification of Depression Using Motor Activity Data and Autoregressive Model. GMDS 2022: 25-32 - [i1]Ahmad Idrissi-Yaghir, Henning Schäfer, Nadja Bauer, Christoph M. Friedrich:
Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback. CoRR abs/2212.05764 (2022)
2010 – 2019
- 2017
- [j1]Klaus Friedrichs, Nadja Bauer, Rainer Martin, Claus Weihs:
A computational study of auditory models in music recognition tasks for normal-hearing and hearing-impaired listeners. EURASIP J. Audio Speech Music. Process. 2017: 7 (2017) - 2014
- [c3]Nadja Bauer, Klaus Friedrichs, Bernd Bischl, Claus Weihs:
Fast Model Based Optimization of Tone Onset Detection by Instance Sampling. ECDA 2014: 461-472 - [c2]Bernd Bischl, Simon Wessing, Nadja Bauer, Klaus Friedrichs, Claus Weihs:
MOI-MBO: Multiobjective Infill for Parallel Model-Based Optimization. LION 2014: 173-186 - 2013
- [p1]Nadja Bauer, Julia Schiffner, Claus Weihs:
Comparison of Classical and Sequential Design of Experiments in Note Onset Detection. Algorithms from and for Nature and Life 2013: 501-509 - 2012
- [c1]Nadja Bauer, Klaus Friedrichs, Dominik Kirchhoff, Julia Schiffner, Claus Weihs:
Tone Onset Detection Using an Auditory Model. GfKl 2012: 315-324
Coauthor Index
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