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Publikationen:

• Christian Klötergens, Tim Dernedde, Lars Schmidt-Thieme, Vijaya Krishna Yalavarthi (2026):
  Mixing It Up: Exploring Mixer Networks for Irregular Multivariate Time Series Forecasting, in Data Science: Foundations and Applications. PAKDD 2026.
• Daniela Thyssens, Tim Dernedde, Wilson Sentanoe, Lars Schmidt-Thieme (2026):
  An Empirical Analysis of Distributional Effects in Learning-Based Routing Systems, in Workshop on Autonomous Machine Intelligence: From Theory to Practice AMIPAKDD2026.
• Tim Dernedde, Daniela Thyssens, Lars Schmidt-Thieme (2025):
  Recurrent State Encoders for Efficient Neural Combinatorial Optimization, in CoRR abs/2509.05084.
• Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  Moco: A Learnable Meta Optimizer for Combinatorial Optimization, in Advances in Knowledge Discovery and Data Mining. PAKDD 2025.
• Daniela Thyssens, Tim Dernedde, Jonas Falkner, Lars Schmidt-Thieme (2023):
  Routing Arena: A Benchmark Suite for Neural Routing Solvers, in arXiv:2310.04140.
• Ahmad Bdeir, Simon Boeder, Tim Dernedde, Kirill Tkachuk, Jonas K. Falkner, Lars Schmidt-Thieme (2021):
  RP-DQN: An Application of Q-Learning to Vehicle Routing Problems, in 44th German Conference on Artificial Intelligence (KI2021): Advances in Artificial Intelligence).