Max Berrendorf

According to our database, Max Berrendorf authored at least 35 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Approximate Answering of Graph Queries.

Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren

Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

Approximate Answering of Graph Queries.

Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren

CoRR, 2023

Cross-Domain Argument Quality Estimation.

Michael Fromm, Max Berrendorf, Evgeniy Faerman, Thomas Seidl

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Benchmark Datasets for Inductive Entity Alignment.

Daniel Obraczka, Max Berrendorf, Charles Tapley Hoyt, Michael Galkin, Erhard Rahm

Dataset, August, 2022

Benchmark Datasets for Inductive Entity Alignment.

Daniel Obraczka, Max Berrendorf, Charles Tapley Hoyt, Michael Galkin, Erhard Rahm

Dataset, August, 2022

Machine learning for managing structured and semi-structured data.

Max Berrendorf

PhD thesis, 2022

Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework.

Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Towards a Holistic View on Argument Quality Prediction.

Michael Fromm, Max Berrendorf, Johanna Reiml, Isabelle Mayerhofer, Siddharth Bhargava, Evgeniy Faerman, Thomas Seidl

CoRR, 2022

A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs.

Charles Tapley Hoyt, Max Berrendorf, Mikhail Galkin, Volker Tresp, Benjamin M. Gyori

CoRR, 2022

An Open Challenge for Inductive Link Prediction on Knowledge Graphs.

Mikhail Galkin, Max Berrendorf, Charles Tapley Hoyt

CoRR, 2022

Reinforcement Learning for Multi-Agent Stochastic Resource Collection.

Niklas Strauß, David Winkel, Max Berrendorf, Matthias Schubert

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations.

Sandra Gilhuber, Max Berrendorf, Yunpu Ma, Thomas Seidl

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), 2022

Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract).

Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Query Embedding on Hyper-Relational Knowledge Graphs.

Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Comparison of Ambulance Redeployment Systems on Real-World Data.

Niklas Strauß, Max Berrendorf, Tom Haider, Matthias Schubert

Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

2021

PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.

Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann

J. Mach. Learn. Res., 2021

On the Generalization of Agricultural Drought Classification from Climate Data.

Julia Gottfriedsen, Max Berrendorf, Pierre Gentine, Markus Reichstein, Katja Weigel, Birgit Hassler, Veronika Eyring

CoRR, 2021

Prediction of soft proton intensities in the near-Earth space using machine learning.

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, Raluca Ilie

CoRR, 2021

Improving Inductive Link Prediction Using Hyper-relational Facts.

Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann

Proceedings of the Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, 2021

Diversity Aware Relevance Learning for Argument Search.

Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman

Proceedings of the Advances in Information Retrieval, 2021

A Critical Assessment of State-of-the-Art in Entity Alignment.

Max Berrendorf, Ludwig Wacker, Evgeniy Faerman

Proceedings of the Advances in Information Retrieval, 2021

Active Learning for Entity Alignment.

Max Berrendorf, Evgeniy Faerman, Volker Tresp

Proceedings of the Advances in Information Retrieval, 2021

Argument Mining Driven Analysis of Peer-Reviews.

Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Argument Mining Driven Analysis of Peer-Reviews Dataset.

Michael Fromm, Max Berrendorf, Evgheniy Faerman, Thomas Seidl

Dataset, December, 2020

Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank.

Max Berrendorf, Evgeniy Faerman, Laurent Vermue, Volker Tresp

CoRR, 2020

Unsupervised Anomaly Detection for X-Ray Images.

Diana Davletshina, Valentyn Melnychuk, Viet Tran, Hitansh Singla, Max Berrendorf, Evgeniy Faerman, Michael Fromm, Matthias Schubert

CoRR, 2020

Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation.

Sandra Obermeier, Max Berrendorf, Peer Kröger

Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods.

Max Berrendorf, Evgeniy Faerman, Laurent Vermue, Volker Tresp

Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Improving Visual Relation Detection using Depth Maps.

Sahand Sharifzadeh, Sina Moayed Baharlou, Max Berrendorf, Rajat Koner, Volker Tresp

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned.

Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl

Proceedings of the Advances in Information Retrieval, 2020

2019

Improving Visual Relation Detection using Depth Maps.

Sahand Sharifzadeh, Max Berrendorf, Volker Tresp

CoRR, 2019

k-Distance Approximation for Memory-Efficient RkNN Retrieval.

Max Berrendorf, Felix Borutta, Peer Kröger

Proceedings of the Similarity Search and Applications - 12th International Conference, 2019

XD-STOD: Cross-Domain Superresolution for Tiny Object Detection.

Michael Fromm, Max Berrendorf, Evgeniy Faerman, Yiyi Chen, Balthasar Schüss, Matthias Schubert

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Spatial Interpolation with Message Passing Framework.

Evgeniy Faerman, Manuell Rogalla, Niklas Strauß, Adrian Krüger, Benedict Blümel, Max Berrendorf, Michael Fromm, Matthias Schubert

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018

Optimal k-Nearest-Neighbor Query Processing via Multiple Lower Bound Approximations.

Christian Beecks, Max Berrendorf

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018