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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).
• Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme (2023):
  Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series, in IEEE International Conference on Big Data (BigData).
• Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme (2023):
  Forecasting Early with Meta Learning, in Proceedings of the 2023 IEEE International Joint Conference on Neural Networks (IEEE IJCNN 2023).
• Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme (2022):
  DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series, in IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA).
• Tolga Akar, Thorben Werner, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme (2022):
  Open Set Recognition for Time Series Classification, in Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference.
• Vijaya Krishna Yalavarthi, Josif Grabocka, Hareesh Mandalapu, Lars Schmidt-Thieme (2019):
  Gait verification using deep learning with a pairwise loss, in 18th International Conference of the Biometrics Special Interest Group (BIOSIG 2019).