Max Berrendorf
Max Berrendorf
Verified email at
Cited by
Cited by
Pykeen 1.0: A python library for training and evaluating knowledge graph embeddings
M Ali, M Berrendorf, CT Hoyt, L Vermue, S Sharifzadeh, V Tresp, ...
Journal of Machine Learning Research 22, 1-6, 2021
Bringing light into the dark: A large-scale evaluation of knowledge graph embedding models under a unified framework
M Ali, M Berrendorf, CT Hoyt, L Vermue, M Galkin, S Sharifzadeh, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 8825 …, 2021
Medium energy electron flux in earth's outer radiation belt (MERLIN): A machine learning model
AG Smirnov, M Berrendorf, YY Shprits, EA Kronberg, HJ Allison, ...
Space Weather 18 (11), e2020SW002532, 2020
Knowledge graph entity alignment with graph convolutional networks: lessons learned
M Berrendorf, E Faerman, V Melnychuk, V Tresp, T Seidl
Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020
Active learning for entity alignment
M Berrendorf, E Faerman, V Tresp
43rd European Conference on Information Retrieval (ECIR-21), 2021
Improving visual relation detection using depth maps
S Sharifzadeh, SM Baharlou, M Berrendorf, R Koner, V Tresp
2020 25th International Conference on Pattern Recognition (ICPR), 3597-3604, 2021
Argument Mining Driven Analysis of Peer-Reviews
M Fromm, E Faerman, M Berrendorf, S Bhargava, R Qi, Y Zhang, ...
Proceedings of the AAAI Conference on Artificial Intelligence 6 (35), 4758-4766, 2020
Improving inductive link prediction using hyper-relational facts
M Ali, M Berrendorf, M Galkin, V Thost, T Ma, V Tresp, J Lehmann
The Semantic Web–ISWC 2021: 20th International Semantic Web Conference, ISWC …, 2021
Interpretable and fair comparison of link prediction or entity alignment methods with adjusted mean rank
M Berrendorf, E Faerman, L Vermue, V Tresp
arXiv preprint arXiv:2002.06914, 2020
Unsupervised anomaly detection for X-ray images
D Davletshina, V Melnychuk, V Tran, H Singla, M Berrendorf, E Faerman, ...
arXiv preprint arXiv:2001.10883, 2020
Query Embedding on Hyper-relational Knowledge Graphs
D Alivanistos, M Berrendorf, M Cochez, M Galkin
International Conference on Learning Representations (ICLR), 2022
On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction Methods
M Berrendorf, E Faerman, L Vermue, V Tresp
arXiv preprint arXiv:2002.06914v3, 2020
An open challenge for inductive link prediction on knowledge graphs
M Galkin, M Berrendorf, CT Hoyt
arXiv preprint arXiv:2203.01520, 2022
Prediction and understanding of soft-proton contamination in XMM-Newton: A machine learning approach
EA Kronberg, F Gastaldello, S Haaland, A Smirnov, M Berrendorf, ...
The Astrophysical Journal 903 (2), 89, 2020
A critical assessment of state-of-the-art in entity alignment
M Berrendorf, L Wacker, E Faerman
Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021
k-distance approximation for memory-efficient RkNN retrieval
M Berrendorf, F Borutta, P Kröger
International Conference on Similarity Search and Applications, 57-71, 2019
Graph alignment networks with node matching scores
E Faerman, O Voggenreiter, F Borutta, T Emrich, M Berrendorf, ...
Proceedings of Advances in Neural Information Processing Systems (NIPS) 2, 2019
A unified framework for rank-based evaluation metrics for link prediction in knowledge graphs
CT Hoyt, M Berrendorf, M Galkin, V Tresp, BM Gyori
arXiv preprint arXiv:2203.07544, 2022
Optimal k-nearest-neighbor query processing via multiple lower bound approximations
C Beecks, M Berrendorf
2018 IEEE International Conference on Big Data (Big Data), 614-623, 2018
Prediction of soft proton intensities in the near-Earth space using machine learning
EA Kronberg, T Hannan, J Huthmacher, M Münzer, F Peste, Z Zhou, ...
The Astrophysical Journal 921 (1), 76, 2021
The system can't perform the operation now. Try again later.
Articles 1–20