Analyzing Political Sentiment on Twitter. - Martin Ringsquandl; Dusan Petkovic (AAAI Spring Symposium: Analyzing Microtext, 2013)

Context-Aware Analytics in MOM Applications. - Martin Ringsquandl; Steffen Lamparter; Raffaello Lepratti (CoRR, 2014)

Semantic-Guided Feature Selection for Industrial Automation Systems. - Martin Ringsquandl; Steffen Lamparter; Sebastian Brandt 001; Thomas Hubauer; Raffaello Lepratti (ISWC (2), 2015)

Knowledge Graph Constraints for Multi-label Graph Classification. - Martin Ringsquandl; Steffen Lamparter; Ingo Thon; Raffaello Lepratti; Peer Kröger (ICDM Workshops, 2016)

Graph-based predictions and recommendations in flexible manufacturing systems. - Martin Ringsquandl; Steffen Lamparter; Raffaello Lepratti (IECON, 2016)

SOMM: Industry Oriented Ontology Management Tool. - Evgeny Kharlamov; Bernardo Cuenca Grau; Ernesto Jiménez-Ruiz; Steffen Lamparter; Gulnar Mehdi; Martin Ringsquandl; Yavor Nenov; Stephan Grimm; Mikhail Roshchin; Ian Horrocks 001 (ISWC (Posters & Demos), 2016)

Capturing Industrial Information Models with Ontologies and Constraints. - Evgeny Kharlamov; Bernardo Cuenca Grau; Ernesto Jiménez-Ruiz; Steffen Lamparter; Gulnar Mehdi; Martin Ringsquandl; Yavor Nenov; Stephan Grimm; Mikhail Roshchin; Ian Horrocks 001 (ISWC (2), 2016)

On event-driven knowledge graph completion in digital factories. - Martin Ringsquandl; Evgeny Kharlamov; Daria Stepanova 001; Steffen Lamparter; Raffaello Lepratti; Ian Horrocks 001; Peer Kröger (IEEE BigData, 2017)

Knowledge Fusion of Manufacturing Operations Data Using Representation Learning. - Martin Ringsquandl; Steffen Lamparter; Raffaello Lepratti; Peer Kröger (APMS (2), 2017)

Event-Enhanced Learning for KG Completion. - Martin Ringsquandl; Evgeny Kharlamov; Daria Stepanova 001; Marcel Hildebrandt; Steffen Lamparter; Raffaello Lepratti; Ian Horrocks 001; Peer Kröger (ESWC, 2018)

Diagnostics of Trains with Semantic Diagnostics Rules. - Evgeny Kharlamov; Ognjen Savkovic; Martin Ringsquandl; Guohui Xiao 001; Gulnar Mehdi; Elem Güzel Kalayci; Werner Nutt; Mikhail Roshchin; Ian Horrocks 001; Thomas A. Runkler (ILP, 2018)

Semantic Diagnostics of Smart Factories. - Ognjen Savkovic; Evgeny Kharlamov; Martin Ringsquandl; Guohui Xiao 001; Gulnar Mehdi; Elem Güzel Kalayci; Werner Nutt; Ian Horrocks 001 (JIST, 2018)

Filling Gaps in Industrial Knowledge Graphs via Event-Enhanced Embedding. - Martin Ringsquandl; Evgeny Kharlamov; Daria Stepanova 001; Marcel Hildebrandt; Steffen Lamparter; Raffaello Lepratti; Ian Horrocks 001; Peer Kröger (ISWC (P&D/Industry/BlueSky), 2018)

Semantic-guided predictive modeling and relational learning within industrial knowledge graphs. - Martin Ringsquandl (2019)

Reasoning on Knowledge Graphs with Debate Dynamics. - Marcel Hildebrandt; Jorge Andres Quintero Serna; Yunpu Ma; Martin Ringsquandl; Mitchell Joblin; Volker Tresp (AAAI, 2020)

Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs. - Marcel Hildebrandt; Jorge Andres Quintero Serna; Yunpu Ma; Martin Ringsquandl; Mitchell Joblin; Volker Tresp (CoRR, 2020)

Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing. - Yushan Liu 002; Marcel Hildebrandt; Mitchell Joblin; Martin Ringsquandl; Volker Tresp (CoRR, 2020)

Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids. - Martin Ringsquandl; Houssem Sellami; Marcel Hildebrandt; Dagmar Beyer; Sylwia Henselmeyer; Sebastian Weber; Mitchell Joblin (CIKM, 2021)

Generating Table Vector Representations. - Aneta Koleva; Martin Ringsquandl; Mitchell Joblin; Volker Tresp (DL4KG@ISWC, 2021)

Neural Multi-hop Reasoning with Logical Rules on Biomedical Knowledge Graphs. - Yushan Liu 002; Marcel Hildebrandt; Mitchell Joblin; Martin Ringsquandl; Rime Raissouni; Volker Tresp (ESWC, 2021)

A New Concept for Explaining Graph Neural Networks. - Anna Himmelhuber; Sonja Zillner; Stephan Grimm; Martin Ringsquandl; Mitchell Joblin; Thomas A. Runkler (NeSy, 2021)

Demystifying Graph Neural Network Explanations. - Anna Himmelhuber; Mitchell Joblin; Martin Ringsquandl; Thomas A. Runkler (PKDD/ECML Workshops (1), 2021)

Combining Sub-symbolic and Symbolic Methods for Explainability. - Anna Himmelhuber; Stephan Grimm; Sonja Zillner; Mitchell Joblin; Martin Ringsquandl; Thomas A. Runkler (RuleML+RR, 2021)

Named Entity Recognition in Industrial Tables using Tabular Language Models. - Aneta Koleva; Martin Ringsquandl; Mark Buckley; Rakebul Hasan; Volker Tresp (EMNLP (Industry Track), 2022)

Task-driven knowledge graph filtering improves prioritizing drugs for repurposing. - Florin Ratajczak; Mitchell Joblin; Martin Ringsquandl; Marcel Hildebrandt (BMC Bioinform., 2022)

Active Learning with Tabular Language Models. - Martin Ringsquandl; Aneta Koleva (CoRR, 2022)

Adversarial Attacks on Tables with Entity Swap. - Aneta Koleva; Martin Ringsquandl; Volker Tresp (VLDB Workshops, 2023)

Wiki-TabNER: Advancing Table Interpretation Through Named Entity Recognition. - Aneta Koleva; Martin Ringsquandl; Ahmed Hatem; Thomas A. Runkler; Volker Tresp (CoRR, 2024)

Wiki-TabNER: Integrating Named Entity Recognition into Wikipedia Tables. - Aneta Koleva; Martin Ringsquandl; Ahmed Hatem; Thomas A. Runkler; Volker Tresp (SIGIR, 2025)