Johannes Kruse

Orcid: 0000-0002-3478-3379

According to our database1, Johannes Kruse authored at least 17 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Disentangling Likes and Dislikes in Personalized Generative Explainable Recommendation.
CoRR, 2024

NORMalize 2024: The Second Workshop on Normative Design and Evaluation of Recommender Systems.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

EB-NeRD a large-scale dataset for news recommendation.
Proceedings of the Recommender Systems Challenge 2024, 2024

RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

NORMalize: A Tutorial on the Normative Design and Evaluation of Information Access Systems.
Proceedings of the 2024 ACM SIGIR Conference on Human Information Interaction and Retrieval, 2024

2023
Machine learning of power grid frequency dynamics and control: prediction, explanation and stochastic modelling
PhD thesis, 2023

Regulatory Changes in Power Systems Explored with Explainable Artificial Intelligence.
CoRR, 2023

NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Creating the next generation of news experience on ekstrabladet.dk with recommender systems.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence.
Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

2022
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI.
Energy Inform., 2022

Physics-inspired machine learning for power grid frequency modelling.
CoRR, 2022

Predicting Dynamic Stability from Static Features in Power Grid Models using Machine Learning.
CoRR, 2022

2021
Revealing drivers and risks for power grid frequency stability with explainable AI.
Patterns, 2021

Secondary control activation analysed and predicted with explainable AI.
CoRR, 2021

Exploring deterministic frequency deviations with explainable AI.
Proceedings of the IEEE International Conference on Communications, 2021

2020
Predictability of Power Grid Frequency.
IEEE Access, 2020


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