Phone, Email:

Phone:	05121 / 883-40378
e-mail:

Publications:

• Wilson Sentanoe, Sreyashi Saha, Yasas Diyanananda, Aqsa Manzoor, Buddhika Dasanayake, Daniela Thyssens (2024):
  Graph2RETA: Graph Neural Networks for Pick-up and Delivery Route Prediction and Arrival Time Estimation, in KI 2024: Advances in Artificial Intelligence. Best Paper Award.
• Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
  Moco: A Learnable Meta Optimizer for Combinatorial Optimization, in arXiv:2402.04915.
• Daniela Thyssens, Tim Dernedde, Jonas Falkner, Lars Schmidt-Thieme (2023):
  Routing Arena: A Benchmark Suite for Neural Routing Solvers, in arXiv:2310.04140.
• Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme (2022):
  Learning to Control Local Search for Combinatorial Optimization., in arXiv preprint arXiv:2206.13181 (accepted at ECML 2022).
• Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme (2022):
  Large Neighborhood Search based on Neural Construction Heuristics., in arXiv preprint arXiv:2205.00772.
• Daniela Thyssens, Jonas K. Falkner, Lars Schmidt-Thieme (2022):
  Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size., in arXiv preprint arXiv:2201.01529.
• Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Lars Schmidt-Thieme, Hadi S Jomaa (2021):
  Do We Really Need Deep Learning Models for Time Series Forecasting?, in arXiv preprint arXiv:2101.02118 (2021).
• Shereen Elsayed, Daniela Thyssens, Shabanaz Chamurally, Arslan Tariq, Hadi S. Jomaa (2020):
  Exploring the influence of data aggregation in parking prediction, in International Conference on Database and Expert Systems Applications (DEXA workshop 2020).