Max Berrendorf

42 papers A* 3B 2Misc 1Journal 21Unranked 13

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Approximate Answering of Graph Queries. CoRR Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren
2023	—	`ch.`	Approximate Answering of Graph Queries. Compendium of Neurosymbolic Artificial Intelligence Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren
2023	—	`conf`	Cross-Domain Argument Quality Estimation. ACL (Findings) Michael Fromm, Max Berrendorf, Evgeniy Faerman, Thomas Seidl
2022	—	`conf`	A Comparison of Ambulance Redeployment Systems on Real-World Data. ICDM (Workshops) Niklas Strauß, Max Berrendorf, Tom Haider, Matthias Schubert
2022	J	`jnl`	A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs. CoRR Charles Tapley Hoyt, Max Berrendorf, Mikhail Galkin, Volker Tresp, Benjamin M. Gyori
2022	—	`conf`	Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations. IAL@PKDD/ECML Sandra Gilhuber, Max Berrendorf, Yunpu Ma, Thomas Seidl
2022	J	`jnl`	An Open Challenge for Inductive Link Prediction on Knowledge Graphs. CoRR Mikhail Galkin, Max Berrendorf, Charles Tapley Hoyt
2022	J	`jnl`	Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. IEEE Trans. Pattern Anal. Mach. Intell. Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
2022	A*	`conf`	Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract). IJCAI Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann
2022	—	`—`	Machine learning for managing structured and semi-structured data. Max Berrendorf
2022	A*	`conf`	Query Embedding on Hyper-Relational Knowledge Graphs. ICLR Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin
2022	—	`conf`	Reinforcement Learning for Multi-Agent Stochastic Resource Collection. ECML/PKDD (4) Niklas Strauß, David Winkel, Max Berrendorf, Matthias Schubert
2022	J	`jnl`	Towards a Holistic View on Argument Quality Prediction. CoRR Michael Fromm, Max Berrendorf, Johanna Reiml, Isabelle Mayerhofer, Siddharth Bhargava, Evgeniy Faerman, Thomas Seidl
2021	—	`conf`	A Critical Assessment of State-of-the-Art in Entity Alignment. ECIR (2) Max Berrendorf, Ludwig Wacker, Evgeniy Faerman
2021	—	`conf`	Active Learning for Entity Alignment. ECIR (1) Max Berrendorf, Evgeniy Faerman, Volker Tresp
2021	A*	`conf`	Argument Mining Driven Analysis of Peer-Reviews. AAAI Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl
2021	—	`conf`	Diversity Aware Relevance Learning for Argument Search. ECIR (2) Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman
2021	J	`jnl`	Improving Inductive Link Prediction Using Hyper-Relational Facts. CoRR Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann
2021	Misc	`conf`	Improving Inductive Link Prediction Using Hyper-relational Facts. ISWC Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann
2021	J	`jnl`	On the Generalization of Agricultural Drought Classification from Climate Data. CoRR Julia Gottfriedsen, Max Berrendorf, Pierre Gentine, Markus Reichstein, Katja Weigel, Birgit Hassler, Veronika Eyring
2021	J	`jnl`	Prediction of soft proton intensities in the near-Earth space using machine learning. CoRR 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
2021	J	`jnl`	PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings. J. Mach. Learn. Res. Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann
2021	J	`jnl`	Query Embedding on Hyper-relational Knowledge Graphs. CoRR Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin
2020	J	`jnl`	A Critical Assessment of State-of-the-Art in Entity Alignment. CoRR Max Berrendorf, Ludwig Wacker, Evgeniy Faerman
2020	J	`jnl`	Active Learning for Entity Alignment. CoRR Max Berrendorf, Evgeniy Faerman, Volker Tresp
2020	J	`jnl`	Argument Mining Driven Analysis of Peer-Reviews. CoRR Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl
2020	J	`jnl`	Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. CoRR Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
2020	J	`jnl`	Diversity Aware Relevance Learning for Argument Search. CoRR Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman
2020	B	`conf`	Improving Visual Relation Detection using Depth Maps. ICPR Sahand Sharifzadeh, Sina Moayed Baharlou, Max Berrendorf, Rajat Koner, Volker Tresp
2020	J	`jnl`	Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank. CoRR Max Berrendorf, Evgeniy Faerman, Laurent Vermue, Volker Tresp
2020	—	`conf`	Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods. WI/IAT Max Berrendorf, Evgeniy Faerman, Laurent Vermue, Volker Tresp
2020	—	`conf`	Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. ECIR (2) Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl
2020	—	`conf`	Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation. WI/IAT Sandra Obermeier, Max Berrendorf, Peer Kröger
2020	J	`jnl`	Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation. CoRR Sandra Obermeier, Max Berrendorf, Peer Kröger
2020	J	`jnl`	PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings. CoRR Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann
2020	J	`jnl`	Unsupervised Anomaly Detection for X-Ray Images. CoRR Diana Davletshina, Valentyn Melnychuk, Viet Tran, Hitansh Singla, Max Berrendorf, Evgeniy Faerman, Michael Fromm, Matthias Schubert
2019	J	`jnl`	Improving Visual Relation Detection using Depth Maps. CoRR Sahand Sharifzadeh, Max Berrendorf, Volker Tresp
2019	J	`jnl`	Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. CoRR Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl
2019	—	`conf`	Spatial Interpolation with Message Passing Framework. ICDM Workshops Evgeniy Faerman, Manuell Rogalla, Niklas Strauß, Adrian Krüger, Benedict Blümel, Max Berrendorf, Michael Fromm, Matthias Schubert
2019	—	`conf`	XD-STOD: Cross-Domain Superresolution for Tiny Object Detection. ICDM Workshops Michael Fromm, Max Berrendorf, Evgeniy Faerman, Yiyi Chen, Balthasar Schüss, Matthias Schubert
2019	B	`conf`	k-Distance Approximation for Memory-Efficient RkNN Retrieval. SISAP Max Berrendorf, Felix Borutta, Peer Kröger
2018	—	`conf`	Optimal k-Nearest-Neighbor Query Processing via Multiple Lower Bound Approximations. IEEE BigData Christian Beecks, Max Berrendorf