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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).
• 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).
• Lukas Brinkmeyer, Rafael Rego Drumond, Johannes Burchert, Lars Schmidt-Thieme (2022):
  Few-Shot Forecasting of Time-Series with Heterogeneous Channels, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.
• Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme (2021):
  Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting, in arXiv.