Workgroup Methods for Missing Data, Model Selection and Model Averaging

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Research interests

  • Natural language processing
  • Deep Learning
  • Reproducibility/Comparability of transfer learning models
  • Epidemiological models and medical applications

Publications (NLP)

  • Aßenmacher, M., Schulze, P. and Heumann, C. (2021). Benchmarking down-scaled (not so large) pre-trained language models. Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021), Düsseldorf, Germany (Online), September 6-9, 2021.
  • Schulze, P., Wiegrebe, S., Thurner, P. W., Heumann, C., Aßenmacher, M. and Wankmüller, S. (2021). Exploring Topic-Metadata Relationships with the STM: A Bayesian Approach. arXiv preprint arXiv:2104.02496.
  • Aßenmacher, M., Corvonato, A. and Heumann, C. (2021). Re-Evaluating GermEval17 Using German Pre-Trained Language Models. Proceedings of the Swiss Text Analytics Conference Winterthur, Switzerland (Online), June 14-16, 2021. [Link to the Slides / Link to the video / Link to the Award]
  • Lebmeier, E., Hou, N., Spann, K., Aßenmacher, M. (2021). Creating a 'customer centricity graph' from unstructured customer feedback. Applied Marketing Analytics., 6(3), 221-229. [Link to AMA / Link to the paper]
  • Meidinger M., and Aßenmacher, M. (2021). A new Benchmark for NLP in Social Sciences: Evaluating the usefulness of pre-trained language models for classifying open-ended survey responses. Proceedings of the 13th International Conference on Agents and Artificial Intelligence (ICAART 2021). Vienna, Austria (Online), February 4-6, 2021, Vol. 2: 866-873. [Link to the poster]
  • Viellieber V. D., and Aßenmacher, M. (2020). Pre-trained language models as knowledge bases for Automotive Complaint Analysis. arXiv preprint arXiv:2012.02558.
  • Guderlei M., and Aßenmacher, M. (2020). Evaluating Unsupervised Representation Learning for Detecting Stances of Fake News. Proceedings of the 28th International Conference on Computational Linguistics (COLING). Barcelona, Spain (Online), December 8-11, 2020: 6339-6349. [Link to the Poster]
  • Aßenmacher, M., and Heumann, C. (2020). On the comparability of Pre-trained Language Models. Proceedings of the 5th Swiss Text Analytics Conference (SwissText) & 16th Conference on Natural Language Processing (KONVENS). Zurich, Switzerland (Online), June 23-25, 2020. [Link to the video]

Publications (Other)

  • Schiergens, T. S., Drefs, M., Dörsch, M., Kühn, F., Albertsmeier, M., Niess, H., Schoenberg, M. B., Aßenmacher, M., Küchenhoff, H., Thasler, W.E., Guba, M. O., Angele, M. K., Rentsch, M., Werner, J., and Andrassy, J. (2021). Prognostic Impact of Pedicle Clamping during Liver Resection for Colorectal Metastases. Cancers., 13(1), 72.
  • Aßenmacher, M., Kaiser, J. C., Zaballa, I., Gasparrini, A., Küchenhoff, H. (2019). Exposure-lag-response associations between lung cancer mortality and radon exposure in German uranium miners. Radiation and Environmental Biophysics, 58(3), 321-336.
  • Sint, A., Lutz, R., Aßenmacher, M., Küchenhoff, H., Kühn, F., Faist, E., Bazhin, A. V., Rentsch, M., Werner, J., Schiergens, T. S. (2019). Monocytic Human Leukocyte Antigen-DR Expression for Prediction of Anastomotic Leak after Colorectal Surgery. Journal of the American College of Surgeons, 229(2), 200-209.
  • Deffner, V., Kreuzer, M., Sobotzki, C., Aßenmacher, M., Güthlin, D., Kaiser, C., Küchenhoff, H., Fenske, N. (2019). Uncertainties in radiation exposure assessment in the Wismut cohort: a preliminary evaluation. BIO Web of Conferences (Vol. 14, p. 03009). EDP Sciences.
  • Küchenhoff, H., Deffner, V., Aßenmacher, M., Neppl, H., Kaiser, C., & Güthlin, D. (2018). Ermittlung der Unsicherheiten der Strahlenexpositionsabschätzung in der Wismut-Kohorte-Teil I-Vorhaben 3616S12223.
  • Brandl, C., Breinlich, V., Stark, K. J., Enzinger, S., Aßenmacher, M., Olden, M., Grassmann, F., Graw, J., Heier, M., Peters, A., Helbig, H., Küchenhoff, H., Weber, B. H. F. , Heid, I. M. (2016). Features of Age-Related Macular Degeneration in the General Adults and Their Dependency on Age, Sex, and Smoking: Results from the German KORA Study. PLOS ONE. doi:/10.1371/journal.pone.0167181.