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Johannes Kruse

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2024
[c8]
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  - conf/chiir/KruseMSTV24
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Johannes Kruse, Lien Michiels, Alain Starke, Nava Tintarev, Sanne Vrijenhoek:
NORMalize: A Tutorial on the Normative Design and Evaluation of Information Access Systems. CHIIR 2024: 422-424
[c7]
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Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen:
EB-NeRD a large-scale dataset for news recommendation. RecSys Challenge 2024: 1-11
[c6]
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Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen:
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations. RecSys 2024: 1195-1199
[c5]
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  - conf/recsys/StarkeVMKT24
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Alain Starke, Sanne Vrijenhoek, Lien Michiels, Johannes Kruse, Nava Tintarev:
NORMalize 2024: The Second Workshop on Normative Design and Evaluation of Recommender Systems. RecSys 2024: 1242-1244
[e1]
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Lien Michiels, Johannes Kruse, Jordi Viader Guerrero, Nava Tintarev:
Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems (NORMalize 2023) co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 19, 2023. CEUR Workshop Proceedings 3639, CEUR-WS.org 2024 [contents]
[i11]
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  - journals/corr/abs-2409-20483
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Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen:
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations. CoRR abs/2409.20483 (2024)
[i10]
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  - journals/corr/abs-2410-03432
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Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen:
EB-NeRD: A Large-Scale Dataset for News Recommendation. CoRR abs/2410.03432 (2024)
[i9]
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  - journals/corr/abs-2410-13248
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Ryotaro Shimizu, Takashi Wada, Yu Wang, Johannes Kruse, Sean O'Brien, Sai Htaung Kham, Linxin Song, Yuya Yoshikawa, Yuki Saito, Fugee Tsung, Masayuki Goto, Julian J. McAuley:
Disentangling Likes and Dislikes in Personalized Generative Explainable Recommendation. CoRR abs/2410.13248 (2024)
2023
[b1]
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  - phd/basesearch/Kruse23
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Johannes Kruse:
Machine learning of power grid frequency dynamics and control: prediction, explanation and stochastic modelling. University of Cologne, Germany, 2023
[c4]
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  - conf/eenergy/PutzKWH023
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Sebastian Pütz, Johannes Kruse, Dirk Witthaut, Veit Hagenmeyer, Benjamin Schäfer:
Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence. e-Energy (Companion) 2023: 26-31
[c3]
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  - conf/recsys/KruseLAF23
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Johannes Kruse, Kasper Lindskow, Michael Riis Andersen, Jes Frellsen:
Creating the next generation of news experience on ekstrabladet.dk with recommender systems. RecSys 2023: 1067-1070
[c2]
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  - conf/recsys/VrijenhoekMKSTG23
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Sanne Vrijenhoek, Lien Michiels, Johannes Kruse, Alain Starke, Nava Tintarev, Jordi Viader Guerrero:
NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems. RecSys 2023: 1252-1254
[i8]
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  - journals/corr/abs-2303-17455
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Sebastian Pütz, Johannes Kruse, Dirk Witthaut, Veit Hagenmeyer, Benjamin Schäfer:
Regulatory Changes in Power Systems Explored with Explainable Artificial Intelligence. CoRR abs/2303.17455 (2023)
2022
[j3]
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  - journals/eninf/PutzSWK22
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Sebastian Pütz, Benjamin Schäfer, Dirk Witthaut, Johannes Kruse:
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI. Energy Inform. 5 (2022)
[i7]
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  - journals/corr/abs-2204-10727
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Sebastian Pütz, Benjamin Schäfer, Dirk Witthaut, Johannes Kruse:
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI. CoRR abs/2204.10727 (2022)
[i6]
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  - journals/corr/abs-2210-09266
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Maurizio Titz, Franz Kaiser, Johannes Kruse, Dirk Witthaut:
Predicting Dynamic Stability from Static Features in Power Grid Models using Machine Learning. CoRR abs/2210.09266 (2022)
[i5]
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  - journals/corr/abs-2211-01481
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Johannes Kruse, Eike Cramer, Benjamin Schäfer, Dirk Witthaut:
Physics-inspired machine learning for power grid frequency modelling. CoRR abs/2211.01481 (2022)
2021
[j2]
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  - journals/patterns/KruseSW21
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Revealing drivers and risks for power grid frequency stability with explainable AI. Patterns 2(11): 100365 (2021)
[c1]
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  - conf/smartgridcomm/KruseSW21
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Exploring deterministic frequency deviations with explainable AI. SmartGridComm 2021: 133-139
[i4]
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  - journals/corr/abs-2106-04341
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Revealing drivers and risks for power grid frequency stability with explainable AI. CoRR abs/2106.04341 (2021)
[i3]
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  - journals/corr/abs-2106-09538
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Exploring deterministic frequency deviations with explainable AI. CoRR abs/2106.09538 (2021)
[i2]
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  - journals/corr/abs-2109-04802
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Secondary control activation analysed and predicted with explainable AI. CoRR abs/2109.04802 (2021)
2020
[j1]
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  - journals/access/KruseSW20
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Predictability of Power Grid Frequency. IEEE Access 8: 149435-149446 (2020)
[i1]
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  - journals/corr/abs-2004-09259
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Johannes Kruse, Benjamin Schäfer, Dirk Witthaut:
Predictability of Power Grid Frequency. CoRR abs/2004.09259 (2020)

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