Martin Ringsquandl
Martin Ringsquandl
Siemens Technology
Verified email at
Cited by
Cited by
Capturing industrial information models with ontologies and constraints
E Kharlamov, BC Grau, E Jiménez-Ruiz, S Lamparter, G Mehdi, ...
The Semantic Web–ISWC 2016: 15th International Semantic Web Conference, Kobe …, 2016
Analyzing political sentiment on Twitter
M Ringsquandl, D Petkovic
2013 AAAI Spring Symposium Series, 2013
Neural multi-hop reasoning with logical rules on biomedical knowledge graphs
Y Liu, M Hildebrandt, M Joblin, M Ringsquandl, R Raissouni, V Tresp
The Semantic Web: 18th International Conference, ESWC 2021, Virtual Event …, 2021
Reasoning on knowledge graphs with debate dynamics
M Hildebrandt, JAQ Serna, Y Ma, M Ringsquandl, M Joblin, V Tresp
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4123-4131, 2020
Semantic-Guided Feature Selection For Industrial Automation Systems
M Ringsquandl, S Lamparter, S Brandt, T Hubauer, R Lepratti
Proceedings of the 14th International Semantic Web Conference, 225-240, 2015
On event-driven knowledge graph completion in digital factories
M Ringsquandl, E Kharlamov, D Stepanova, S Lamparter, R Lepratti, ...
2017 IEEE International Conference on Big Data (Big Data), 1676-1681, 2017
Assessing IFC classes with means of geometric deep learning on different graph encodings
F Collins, A Braun, M Ringsquandl, D Hall, A Borrmann
Proc. of the 2021 European Conference on Computing in Construction, 2021
Control apparatus of an automation system
T Hubauer, S Lamparter, M Ringsquandl, M Roshchin
US Patent 10,545,967, 2020
Event-enhanced learning for KG completion
M Ringsquandl, E Kharlamov, D Stepanova, M Hildebrandt, S Lamparter, ...
The Semantic Web: 15th International Conference, ESWC 2018, Heraklion, Crete …, 2018
Knowledge fusion of manufacturing operations data using representation learning
M Ringsquandl, S Lamparter, R Lepratti, P Kröger
Advances in Production Management Systems. The Path to Intelligent …, 2017
Power to the relational inductive bias: Graph neural networks in electrical power grids
M Ringsquandl, H Sellami, M Hildebrandt, D Beyer, S Henselmeyer, ...
Proceedings of the 30th ACM International Conference on Information …, 2021
Task-driven knowledge graph filtering improves prioritizing drugs for repurposing
F Ratajczak, M Joblin, M Ringsquandl, M Hildebrandt
BMC bioinformatics 23 (1), 84, 2022
Graph-based predictions and recommendations in flexible manufacturing systems
M Ringsquandl, S Lamparter, R Lepratti
IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society …, 2016
Diagnostics of trains with semantic diagnostics rules
E Kharlamov, O Savković, M Ringsquandl, G Xiao, G Mehdi, EG Kalayc, ...
Inductive Logic Programming: 28th International Conference, ILP 2018 …, 2018
Shape encoding for semantic healing of design models and knowledge transfer to scan-to-BIM
FC Collins, M Ringsquandl, A Braun, DM Hall, A Borrmann
Proceedings of the institution of civil engineers-smart infrastructure and …, 2022
Demystifying graph neural network explanations
A Himmelhuber, M Joblin, M Ringsquandl, T Runkler
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
Filling gaps in industrial knowledge graphs via event-enhanced embedding
M Ringsquandl, E Kharlamov, D Stepanova, M Hildebrandt, S Lamparter, ...
17th International Semantic Web Conference, 2018
Named Entity Recognition in Industrial Tables using Tabular Language Models
A Koleva, M Ringsquandl, M Buckley, R Hasan, V Tresp
Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022
Analysis of the attention in tabular language models
A Koleva, M Ringsquandl, V Tresp
NeurIPS 2022 First Table Representation Workshop, 2022
Combining Sub-symbolic and Symbolic Methods for Explainability
A Himmelhuber, S Grimm, S Zillner, M Joblin, M Ringsquandl, T Runkler
Rules and Reasoning: 5th International Joint Conference, RuleML+ RR 2021 …, 2021
The system can't perform the operation now. Try again later.
Articles 1–20