Lehr- und Forschungseinheit für Datenbanksysteme
print


Breadcrumb Navigation


Content
Max Berrendorf

Max Berrendorf

Research Assistant

Contact

Ludwig-Maximilians-Universität München
Lehrstuhl für Datenbanksysteme und Data Mining
Oettingenstraße 67
80538 München
Germany

Room: F 110
Phone: +49-89-2180-9305

Research Interest

  • Deep Learning
  • Relational Learning
  • Knowledge Graphs

Teaching

  1. WS 21/22  ESG "Algorithm Design"
  2. SS 21        Praktikum Big Data Science
  3. WS 20/21  ESG "System Development"
  4. SS 20        Praktikum Big Data Science
  5. WS 19/20  Oberseminar
  6. WS 19/20  Master Seminar "Deep Learning for Graphs"
  7. SS 19        Oberseminar
  8. SS 19        Master Seminar "Recent Developments in Deep Learning"
  9. SS 19        Praktikum Big Data Science
  10. WS 18/19  Knowledge Discovery and Data Mining I
  11. SS 18        Praktikum Big Data Science
The projects from Praktikum Big Data Science are also featured at a dedicated website.

Supervised Theses

  1. Transfer Learning for 3D Object Detection in Point Clouds
  2. Adapting Knowledge Graph Structure for Entity Alignment
  3. Language-Aware Entity Alignment
  4. Knowledge Graph Alignment with Reference Points
  5. Negative Sampling Strategies For Link Prediction in Knowledge Graphs
  6. Active Learning for Entity Alignment
  7. Knowledge Graph Fusion using Cycle Consistency
  8. Nonlinear k-Distance Approximation
  9. Memory-Efficient k-Distance Approximation for RkNN Retrieval
  10. Optimisation-Based Correlation Clustering Using Hough Transform

Publications

  1. Mehdi Ali*, Max Berrendorf*, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, and Jens Lehmann.
    Improving Inductive Link Prediction Using Hyper-Relational Facts
    The 20th International Semantic Web Conference (ISWC'21)
  2. Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin
    Query Embedding on Hyper-relational Knowledge Graphs
    arXiv 2021
  3. Elena A. Kronberg, Tanveer Hannan, Jens Huthmacher, Marcus Münzer, Florian Peste, Ziyang Zhou, Max Berrendorf, Evgeniy Faerman, Fabio Gastaldello, Simona Ghizzardi, Philippe Escoubet, Stein Haaland, Artem Smirnov, Nithin Sivadas, Robert C. Allen, Andrea Tiengo, and Raluca Ilie.
    Prediction of soft proton intensities in the near-Earth space using machine learning
    arXiv 2021
  4. Mehdi Ali*, Max Berrendorf*, Charles Tapley Hoyt*, Laurent Vermue*, Sahand Sharifzadeh, Volker Tresp, and Jens Lehmann.
    "PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings"
    Journal of Machine Learning Research (JMLR), 22(82): 1-6
  5. Max Berrendorf*, Evgeniy Faerman*, and Volker Tresp.
    "Active Learning for Entity Alignment"
    43rd European Conference on Information Retrieval (ECIR-21)
  6. Max Berrendorf, Ludwig Wacker, Evgeniy Faerman.
    "A Critical Assessment of State-of-the-Art in Entity Alignment"
    43rd European Conference on Information Retrieval (ECIR-21)
  7. Michael Fromm*, Max Berrendorf*, Sandra Obermeier, Thomas Seidl, and Evgeniy Faerman.
    "Diversity Aware Relevance Learning for Argument Search"
    43rd European Conference on Information Retrieval (ECIR-21)
  8. Max Berrendorf, Evgeniy Faerman, Laurent Vermue, and Volker Tresp.
    "On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction Methods"
    arXiv 2020
  9. Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, and Thomas Seidl.
    "Argument Mining Driven Analysis of Peer-Reviews"
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21)
    DOI
  10. Sandra Obermeier, Max Berrendorf, Peer Kröger.
    "Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation"
    The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'20)
  11. Max Berrendorf, Evgeniy Faerman, Laurent Vermue, and Volker Tresp.
    "Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods"
    The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'20)
  12. Elena A. Kronberg, Fabio Gastaldello, Stein Haaland, Artem Smirnov, Max Berrendorf, Simona Ghizzardi, K. D. Kuntz, Nithin Sivadas, Robert C. Allen, Andrea Tiengo, Raluca Ilie, Yu Huang, and Lynn Kistler.
    "Prediction and Understanding of Soft-proton Contamination in XMM-Newton: A Machine Learning Approach"
    The Astrophysical Journal
  13. Mehdi Ali, Max Berrendorf*, Charles Tapley Hoyt*, Laurent Vermue*, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, and Jens Lehmann
    "Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework"
    arXiv 2020
  14. Sahand Sharifzadeh, Sina Moayed Baharlou*, Max Berrendorf*, Rajat Koner, and Volker Tresp.
    "Improving Visual Relation Detection using Depth Maps"
    25th International Conference on Pattern Recognition (ICPR2020)
  15. Artem Smirnov, Max Berrendorf, Yuri Shprits, Elena A. Kronberg, Hayley J Allison, Nikita A Aseev, Irina S. Zhelavskaya, Steven K. Morley, Geoffrey D. Reeves, Matthew R. Carver, and Frederic Effenberger
    "Medium Energy Electron Flux in Earth's Outer Radiation Belt (MERLIN): A Machine Learning Model"
    Space Weather Journal
  16. Diana Davletshina, Valentyn Melnychuk, Viet Tran, Hitansh Singla, Max Berrendorf, Evgeniy Faerman, Michael Fromm, and Matthias Schubert.
    "Unsupervised Anomaly Detection for X-Ray Images"
    arXiv 2020
  17. Max Berrendorf*, Evgeniy Faerman*, and Volker Tresp.
    "Active Learning for Entity Alignment"
    The Fifth International Workshop on Deep Learning for Graphs (DL4G@WWW2020)
  18. Max Berrendorf, Evgeniy Faerman, Laurent Vermue and and Volker Tresp.
    "Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank"
    The Fifth International Workshop on Deep Learning for Graphs (DL4G@WWW2020)
  19. Artem Smirnov, Elena A. Kronberg, Max Berrendorf, Steven Morley, and Yuri Shprits
    "Medium energy electron fluxes in Earth’s outer radiation belt: a machine learning model"

    AGU Fall Meeting 2019
  20. Evgeniy Faerman, Otto Voggenreiter, Felix Borutta, Tobias Emrich, Max Berrendorf, and Matthias Schubert.
    "Graph Alignment Networks with Node Matching Scores"
    .
    Graph Representation Learning (NeuRIPS 2019 Workshop)

  21. E. Kronberg, R. Ilie, A. Smirnov, F. Gastaldello, S. Haaland, M. Berrendorf et al.
    "Prediction of soft protons in the near-Earth space using machine learning."
    Poster presented at Machine Learning in Heliophysics, Amsterdam, Netherlands.
  22. Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, and Thomas Seidl.
    "Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned".
    42nd European Conference on Information Retrieval (ECIR 2020)
  23. Michael Fromm, Max Berrendorf, Evgeniy Faerman, Yiyi Chen, Balthasar Schüss, and Matthias Schubert.
    "XD-STOD: Cross-Domain Superresolution for Tiny Object Detection".
    Deep Spatial 2019 (ICDM Workshop)
  24. Evgeniy Faerman, Manuel Rogalla, Niklas Strauß, Adrian Krüger, Benedict Blümel, Max Berrendorf, Michael Fromm, and Matthias Schubert.
    "Spatial Interpolation with Message Passing Framework".
    Deep Spatial 2019 (ICDM Workshop)
  25. Max Berrendorf, Felix Borutta and Peer Kröger.
    "k-Distance Approximation for Memory-Efficient RkNN Retrieval"
    .
    SISAP 2019.
  26. Christian Beecks and Max Berrendorf.
    "Optimal k-nearest-neighbor query processing via multiple lower bound approximations."

    IEEE BigData 2018

Academic Service

Reviewing for AAAI (AAAI'20), BTW (BTW'19), CCN (CCN'19), DL4KG Workshop (DL4KG@ISWC'21, DL4KG@ESWC'20), ECML/PKDD (ECML-PKDD'19, ECML-PKDD'20), EDBT/ICDT (EDBT/ICDT'18), NeurIPS (NeurIPS'21, NeurIPS'20, NeurIPS'19), ICLR (ICLR'20), ICML (ICML'21, ICML'20, ICML'19), IJCAI (IJCAI'19), and ML4H Workshop (ML4H@NeurIPS'19).

Projects

  • MCML: Machine Learning for Knowledge Graphs (Project Website)
  • Efficient Database Techniques for Reverse k-Nearest Neighbor Search (DFG)