journal articles

conference papers

workshop papers

  • [w8] Lukas Galke, Yoav Ram, Limor Raviv (2022). Emergent communication for understanding human language evolution: What’s missing?. Emergent Communication workshop at The Tenth International Conference on Learning Representations (ICLR 2022)

  • [w7] Lukas Galke, Eva Seidlmayer, Gavin Lüdemann, Lisa Langnickel, Tetyana Melnychuk, Konrad U Förstner, Klaus Tochtermann, Carsten Schultz (2021). COVID-19++: A Citation-Aware Covid-19 Dataset for the Analysis of Research Dynamics. In 2021 IEEE International Conference on Big Data (Big Data). IEEE.

  • [w6] Eva Seidlmayer, Jakob Voß, Tatyana Melnychuk, Lukas Galke, Klaus Tochtermann, Carsten Schultz, Konrad U. Förstner: ORCID for Wikidata — Data enrichment for scientometric applications, Wikidata workshop @ ISWC 2020.

  • [w5] Eva Seidlmayer, Lukas Galke, Tatyana Melnychuk, Carsten Schultz, Klaus Tochtermann, Konrad U. Förstner (2019): Take it Personally — A Python library for enrichment in informetrical applications. Posters&Demos @ SEMANTICS 2019.

  • [w4] Lukas Galke, Iacopo Vagliano, Ansgar Scherp (2019). Can Graph Neural Networks Go „Online“? An Analysis of Pretraining and Inference. Representation Learning on Graphs and Manifolds workshop @ ICLR 2019.

  • [w3] Iacopo Vagliano, Lukas Galke, Florian Mai, Ansgar Scherp (2018). Using Adversarial Autoencoders for Multi-Modal Automatic Playlist Continuation. RecSys Challenge workshop @ RecSys’18.

  • [w2] Lukas Galke, Gunnar Gerstenkorn, Ansgar Scherp (2018). A Case Study of Closed-Domain Response Suggestion with Limited Training Data. Text-based Information Retrieval workshop @ DEXA’18.

  • [w1] Lukas Galke, Ahmed Saleh, Ansgar Scherp (2017). Word Embeddings for Practical Information Retrieval. In INFORMATIK 2017. Gesellschaft für Informatik, Bonn. (S. 2155-2167).

(extended) abstracts

  • [a2] Lukas Galke (2022). Representation Learning for Texts and Graphs: A Unified Perspective On Efficiency, Multimodality, and Adaptability [selected PhD thesis abstract]. IEEE Intelligent Informatics Bulletin, 22(1), 52.

  • [a1] Lukas Galke, Florian Mai, Ansgar Scherp (2019): What If We Encoded Words as Matrices and Used Matrix Multiplication as Composition Function [extended abstract]. INFORMATIK 2019. GI.


  • Lukas Galke (2023). Representation Learning for Texts and Graphs: A Unified Perspective On Efficiency, Multimodality, and Adaptability. Number 2023/1 in Kiel Computer Science Series. Department of Computer Science, 2023. Dissertation, Faculty of Engineering, Kiel University.