| Tensorforce: A tensorflow library for applied reinforcement learning M Schaarschmidt, A Kuhnle, K Fricke Web page, 2017 | 184* | 2017 |
| Personality and self-reported preference for music genres and attributes in a German-speaking sample KR Fricke, PY Herzberg Journal of Research in Personality 68, 114-123, 2017 | 59 | 2017 |
| The self-congruity effect of music. DM Greenberg, SC Matz, HA Schwartz, KR Fricke Journal of Personality and Social Psychology 121 (1), 137, 2021 | 52 | 2021 |
| Lift: Reinforcement learning in computer systems by learning from demonstrations M Schaarschmidt, A Kuhnle, B Ellis, K Fricke, F Gessert, E Yoneki arXiv preprint arXiv:1808.07903, 2018 | 47 | 2018 |
| Computer-based music feature analysis mirrors human perception and can be used to measure individual music preference KR Fricke, DM Greenberg, PJ Rentfrow, PY Herzberg Journal of Research in Personality 75, 94-102, 2018 | 47 | 2018 |
| Measuring musical preferences from listening behavior: Data from one million people and 200,000 songs KR Fricke, DM Greenberg, PJ Rentfrow, PY Herzberg Psychology of Music 49 (3), 371-381, 2021 | 33 | 2021 |
| RLgraph: Modular Computation Graphs for Deep Reinforcement Learning M Schaarschmidt, S Mika, K Fricke, E Yoneki Proceedings of the 2nd Conference on Systems and Machine Learning (SysML), 2019 | 24* | 2019 |
| Tensorforce: a TensorFlow library for applied reinforcement learning. 2017 A Kuhnle, M Schaarschmidt, K Fricke Available online: tensorforce. readthedocs. io (accessed on 21 December 2021), 2019 | 14 | 2019 |
| Validation of the Flemish version of the Quality of Life in Short Stature Youth (QoLISSY) questionnaire AC Rohenkohl, J De Schepper, J Vanderfaeillie, K Fricke, S Hendrickx, ... Acta Clinica Belgica 69 (3), 177-182, 2014 | 13 | 2014 |
| Normierung der deutschen Fassung der Highly Sensitive Person Scale (HSPS-G)–Selbstbeurteilungsskala an einer deutschsprachigen Stichprobe PY Herzberg, KR Fricke, S Konrad PPmP-Psychotherapie· Psychosomatik· Medizinische Psychologie 72 (03/04), 108-116, 2022 | 8 | 2022 |
| Wield: Systematic reinforcement learning with progressive randomization M Schaarschmidt, K Fricke, E Yoneki arXiv preprint arXiv:1909.06844, 2019 | 4 | 2019 |
| World-models for bitrate streaming H Brown, K Fricke, E Yoneki Applied Sciences 10 (19), 6685, 2020 | 3 | 2020 |
| Decreasing Stress Through a Spatial Audio and Immersive 3D Environment: A Pilot Study With Implications for Clinical and Medical Settings DM Greenberg, E Bodner, A Shrira, KR Fricke Music & Science 4, 2059204321993992, 2021 | 2 | 2021 |
| Know your big data: De-biasing subsamples of large datasets for personality research using importance sampling and kNN matching K Fricke, P Herzberg PsyArXiv, 2019 | 1 | 2019 |
| Rethinking musical preferences: Introducing the Test of Attribute Preferences (TAP) DJ Grüning, K Fricke, PJ Rentfrow, YDM Greenberg | | 2024 |
| Using dynamic item response theory and machine learning based on natural language processing to improve the reliability of the Operant Motive Test. D Scheffer, J Klöpper, N Scheffer, G Rose, T Fraunholz, P Klein, KR Fricke, ... Motivation Science, 2024 | | 2024 |
| Norms of the German Version of the Highly Sensitive Person Scale (HSPS-G)-Self-Assessment Scale on a German-Speaking Sample PY Herzberg, KR Fricke, S Konrad Psychotherapie, Psychosomatik, Medizinische Psychologie 72 (3-04), 108-116, 2021 | | 2021 |
| Measuring Individual Music Feature Preference from Self-report, Audio-based Assessment, and Actual Listening Behavior K Fricke Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Fakultät für …, 2018 | | 2018 |
| Genres are out and attributes are in: Introducing an advanced test of musical preferences DJ Gruning, K Fricke, PJ Rentfrow, YDM Greenberg OSF, 0 | | |
Michael SchaarschmidtResearch Scientist, Isomorphic LabsΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cam.ac.uk