| Do we really need deep learning models for time series forecasting? S Elsayed, D Thyssens, A Rashed, HS Jomaa, L Schmidt-Thieme arXiv preprint arXiv:2101.02118, 2021 | 126 | 2021 |
| Do we really need deep learning models for time series forecasting? arXiv 2021 S Elsayed, D Thyssens, A Rashed, HS Jomaa, L Schmidt-Thieme arXiv preprint arXiv:2101.02118, 0 | 14 | |
| Learning to control local search for combinatorial optimization JK Falkner, D Thyssens, A Bdeir, L Schmidt-Thieme Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 11 | 2022 |
| Large neighborhood search based on neural construction heuristics JK Falkner, D Thyssens, L Schmidt-Thieme arXiv preprint arXiv:2205.00772, 2022 | 6 | 2022 |
| Do we really need deep learning models for time series forecasting?, 2021 S Elsayed, D Thyssens, A Rashed, HS Jomaa, L Schmidt-Thieme URL https://arxiv. org/abs/2101 2118, 2021 | 6 | 2021 |
| Supervised permutation invariant networks for solving the CVRP with bounded fleet size D Thyssens, J Falkner, L Schmidt-Thieme arXiv preprint arXiv:2201.01529, 2022 | 3 | 2022 |
| Exploring the influence of data aggregation in parking prediction S Elsayed, D Thyssens, S Chamurally, A Tariq, HS Jomaa Database and Expert Systems Applications: DEXA 2020 International Workshops …, 2020 | 1 | 2020 |
| Moco: A Learnable Meta Optimizer for Combinatorial Optimization T Dernedde, D Thyssens, S Dittrich, M Stubbemann, L Schmidt-Thieme arXiv preprint arXiv:2402.04915, 2024 | | 2024 |
| Routing Arena: A Benchmark Suite for Neural Routing Solvers D Thyssens, T Dernedde, JK Falkner, L Schmidt-Thieme arXiv preprint arXiv:2310.04140, 2023 | | 2023 |
| DeepStay: Stay Region Extraction from Location Trajectories using Weak Supervision C Löwens, D Thyssens, E Andersson, C Jenkins, L Schmidt-Thieme 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | | 2023 |
