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Publikationen:

• Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme (2024):
  GraFITi: Graphs for Forecasting Irregularly Sampled Time SeriesTripletformer for Probabilistic Interpolation of Irregularly sampled Time Series, in Proceedings of the AAAI conference on artificial intelligence (AAAI, oral).
• Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz (2022):
  Multi-script handwritten digit recognition using multi-task learning., .
• Dr. Nghia Duong-Trung, Stefan Born, JongWoo Kim, Marie-Therese Schermeyer, Katharina Paulick, Maxim Borisyak, Ernesto Martinez, Mariano Nicolas Cruz-Bournazou, Randolf Scholz, Lars Schmidt-Thieme, Peter Neubauer,, Thorben Werner (2022):
  When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development, Biochemical Engineering Journal .
• Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz, Lars Schmidt-Thieme (2021):
  Deep Metric Learning for Ground Images, in arXiv preprint arXiv:2109.01569 (2021).
• Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz (2022):
  Multi-script handwritten digit recognition using multi-task learning., in J. Intell. Fuzzy Syst., pp. 355-364.
• Randolf Scholz, Josif Grabocka, Lars Schmidt-Thieme (2019):
  Learning surrogate losses, in arXiv preprint arXiv:1905.10108 (2019).
• Lukas Brinkmeyer, Rafael Rêgo Drumond, Randolf Scholz, Josif Grabocka, Lars Schmidt-Thieme (2019):
  Chameleon: Learning Model Initializations Across Tasks With Different Schemas, in arXiv preprint arXiv:1909.13576 (2019).