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Max Berrendorf
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2020 – today
- 2023
- [c19]Michael Fromm, Max Berrendorf, Evgeniy Faerman, Thomas Seidl:
Cross-Domain Argument Quality Estimation. ACL (Findings) 2023: 13435-13448 - [p1]Michael Cochez
, Dimitrios Alivanistos, Erik Arakelyan
Approximate Answering of Graph Queries. Compendium of Neurosymbolic Artificial Intelligence 2023: 373-386 - [i19]Michael Cochez
Approximate Answering of Graph Queries. CoRR abs/2308.06585 (2023) - 2022
- [b1]Max Berrendorf:
Machine learning for managing structured and semi-structured data. Ludwig Maximilian University of Munich, Germany, 2022 - [j2]Mehdi Ali
Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8825-8845 (2022) - [c18]Niklas Strauß, Max Berrendorf, Tom Haider, Matthias Schubert:
A Comparison of Ambulance Redeployment Systems on Real-World Data. ICDM (Workshops) 2022: 1-8 - [c17]Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin:
Query Embedding on Hyper-Relational Knowledge Graphs. ICLR 2022 - [c16]Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann:
Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract). IJCAI 2022: 5259-5263 - [c15]Sandra Gilhuber, Max Berrendorf, Yunpu Ma, Thomas Seidl:
Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations. IAL@PKDD/ECML 2022: 43-48 - [c14]Niklas Strauß
Reinforcement Learning for Multi-Agent Stochastic Resource Collection. ECML/PKDD (4) 2022: 200-215 - [d3]Daniel Obraczka
Benchmark Datasets for Inductive Entity Alignment. Version v0.1.0. Zenodo, 2022 [all versions] - [d2]Daniel Obraczka
Benchmark Datasets for Inductive Entity Alignment. Version v0.1.1. Zenodo, 2022 [all versions] - [i18]Mikhail Galkin, Max Berrendorf, Charles Tapley Hoyt:
An Open Challenge for Inductive Link Prediction on Knowledge Graphs. CoRR abs/2203.01520 (2022) - [i17]Charles Tapley Hoyt, Max Berrendorf, Mikhail Galkin, Volker Tresp, Benjamin M. Gyori:
A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs. CoRR abs/2203.07544 (2022) - [i16]Michael Fromm, Max Berrendorf, Johanna Reiml, Isabelle Mayerhofer, Siddharth Bhargava, Evgeniy Faerman, Thomas Seidl:
Towards a Holistic View on Argument Quality Prediction. CoRR abs/2205.09803 (2022) - 2021
- [j1]Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann:
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings. J. Mach. Learn. Res. 22: 82:1-82:6 (2021) - [c13]Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl:
Argument Mining Driven Analysis of Peer-Reviews. AAAI 2021: 4758-4766 - [c12]Max Berrendorf
A Critical Assessment of State-of-the-Art in Entity Alignment. ECIR (2) 2021: 18-32 - [c11]Max Berrendorf, Evgeniy Faerman, Volker Tresp:
Active Learning for Entity Alignment. ECIR (1) 2021: 48-62 - [c10]Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman:
Diversity Aware Relevance Learning for Argument Search. ECIR (2) 2021: 264-271 - [c9]Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma
Improving Inductive Link Prediction Using Hyper-relational Facts. ISWC 2021: 74-92 - [i15]Elena A. Kronberg, Tanveer Hannan, Jens Huthmacher, Marcus Münzer, Florian Peste, Ziyang Zhou, Max Berrendorf, Evgeniy Faerman, Fabio Gastaldello, Simona Ghizzardi
Prediction of soft proton intensities in the near-Earth space using machine learning. CoRR abs/2105.15108 (2021) - [i14]Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin:
Query Embedding on Hyper-relational Knowledge Graphs. CoRR abs/2106.08166 (2021) - [i13]Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, Jens Lehmann:
Improving Inductive Link Prediction Using Hyper-Relational Facts. CoRR abs/2107.04894 (2021) - [i12]Julia Gottfriedsen, Max Berrendorf, Pierre Gentine, Markus Reichstein, Katja Weigel, Birgit Hassler, Veronika Eyring:
On the Generalization of Agricultural Drought Classification from Climate Data. CoRR abs/2111.15452 (2021) - 2020
- [c8]Max Berrendorf
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. ECIR (2) 2020: 3-11 - [c7]Sahand Sharifzadeh, Sina Moayed Baharlou
Improving Visual Relation Detection using Depth Maps. ICPR 2020: 3597-3604 - [c6]Max Berrendorf
Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods. WI/IAT 2020: 371-374 - [c5]Sandra Obermeier, Max Berrendorf
Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation. WI/IAT 2020: 387-390 - [d1]Michael Fromm
Argument Mining Driven Analysis of Peer-Reviews Dataset. Zenodo, 2020 - [i11]Max Berrendorf
Active Learning for Entity Alignment. CoRR abs/2001.08943 (2020) - [i10]Diana Davletshina, Valentyn Melnychuk
Unsupervised Anomaly Detection for X-Ray Images. CoRR abs/2001.10883 (2020) - [i9]Max Berrendorf
Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank. CoRR abs/2002.06914 (2020) - [i8]Mehdi Ali, Max Berrendorf
Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. CoRR abs/2006.13365 (2020) - [i7]Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann:
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings. CoRR abs/2007.14175 (2020) - [i6]Max Berrendorf, Ludwig Wacker, Evgeniy Faerman:
A Critical Assessment of State-of-the-Art in Entity Alignment. CoRR abs/2010.16314 (2020) - [i5]Sandra Obermeier, Max Berrendorf, Peer Kröger:
Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation. CoRR abs/2011.01773 (2020) - [i4]Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman:
Diversity Aware Relevance Learning for Argument Search. CoRR abs/2011.02177 (2020) - [i3]Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl:
Argument Mining Driven Analysis of Peer-Reviews. CoRR abs/2012.07743 (2020)
2010 – 2019
- 2019
- [c4]Evgeniy Faerman, Manuell Rogalla, Niklas Strauß, Adrian Krüger, Benedict Blümel
Spatial Interpolation with Message Passing Framework. ICDM Workshops 2019: 135-141 - [c3]Michael Fromm, Max Berrendorf
XD-STOD: Cross-Domain Superresolution for Tiny Object Detection. ICDM Workshops 2019: 142-148 - [c2]Max Berrendorf
k-Distance Approximation for Memory-Efficient RkNN Retrieval. SISAP 2019: 57-71 - [i2]Sahand Sharifzadeh, Max Berrendorf
Improving Visual Relation Detection using Depth Maps. CoRR abs/1905.00966 (2019) - [i1]Max Berrendorf
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. CoRR abs/1911.08342 (2019) - 2018
- [c1]Christian Beecks, Max Berrendorf
Optimal k-Nearest-Neighbor Query Processing via Multiple Lower Bound Approximations. IEEE BigData 2018: 614-623
Coauthor Index
aka: Evgeniy Faerman
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