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ORCIDMartin Ringsquandl
- > Home > Persons > Martin Ringsquandl
Publications
- 2022
[j1]Florin Ratajczak
, Mitchell Joblin, Martin Ringsquandl, Marcel Hildebrandt:
Task-driven knowledge graph filtering improves prioritizing drugs for repurposing. BMC Bioinform. 23(1): 84 (2022)- 2021
- [c19]Martin Ringsquandl, Houssem Sellami, Marcel Hildebrandt, Dagmar Beyer, Sylwia Henselmeyer, Sebastian Weber, Mitchell Joblin:
Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids. CIKM 2021: 1538-1547 - [c18]Aneta Koleva, Martin Ringsquandl, Mitchell Joblin, Volker Tresp:
Generating Table Vector Representations. DL4KG@ISWC 2021 - [c17]Yushan Liu, Marcel Hildebrandt, Mitchell Joblin, Martin Ringsquandl, Rime Raissouni, Volker Tresp:
Neural Multi-hop Reasoning with Logical Rules on Biomedical Knowledge Graphs. ESWC 2021: 375-391 - [c16]Anna Himmelhuber, Sonja Zillner, Stephan Grimm, Martin Ringsquandl, Mitchell Joblin, Thomas A. Runkler:
A New Concept for Explaining Graph Neural Networks. NeSy 2021: 1-5 - [c15]Anna Himmelhuber, Mitchell Joblin, Martin Ringsquandl, Thomas A. Runkler:
Demystifying Graph Neural Network Explanations. PKDD/ECML Workshops (1) 2021: 67-75 - [c14]Anna Himmelhuber, Stephan Grimm, Sonja Zillner, Mitchell Joblin, Martin Ringsquandl, Thomas A. Runkler:
Combining Sub-symbolic and Symbolic Methods for Explainability. RuleML+RR 2021: 172-187 - [i10]Yushan Liu, Marcel Hildebrandt, Mitchell Joblin, Martin Ringsquandl, Rime Raissouni, Volker Tresp:
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs. CoRR abs/2103.10367 (2021) - [i9]Martin Ringsquandl, Houssem Sellami, Marcel Hildebrandt, Dagmar Beyer, Sylwia Henselmeyer, Sebastian Weber, Mitchell Joblin:
Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids. CoRR abs/2109.03604 (2021) - [i7]Aneta Koleva, Martin Ringsquandl, Mitchell Joblin, Volker Tresp:
Generating Table Vector Representations. CoRR abs/2110.15132 (2021) - [i6]Anna Himmelhuber, Mitchell Joblin, Martin Ringsquandl, Thomas A. Runkler:
Demystifying Graph Neural Network Explanations. CoRR abs/2111.12984 (2021) - [i5]Anna Himmelhuber, Stephan Grimm, Sonja Zillner, Mitchell Joblin, Martin Ringsquandl, Thomas A. Runkler:
Combining Sub-Symbolic and Symbolic Methods for Explainability. CoRR abs/2112.01844 (2021) - 2020
- [c13]Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma, Martin Ringsquandl, Mitchell Joblin, Volker Tresp:
Reasoning on Knowledge Graphs with Debate Dynamics. AAAI 2020: 4123-4131 - [i4]Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma, Martin Ringsquandl, Mitchell Joblin, Volker Tresp:
Reasoning on Knowledge Graphs with Debate Dynamics. CoRR abs/2001.00461 (2020) - [i3]Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma, Martin Ringsquandl, Mitchell Joblin, Volker Tresp:
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs. CoRR abs/2001.03436 (2020) - [i2]Yushan Liu, Marcel Hildebrandt, Mitchell Joblin, Martin Ringsquandl, Volker Tresp:
Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing. CoRR abs/2007.05292 (2020)
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