| Self-supervised learning for semi-supervised time series classification S Jawed, J Grabocka, L Schmidt-Thieme Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia …, 2020 | 76 | 2020 |
| MultiRec: A multi-relational approach for unique item recommendation in auction systems A Rashed, S Jawed, L Schmidt-Thieme, A Hintsches Proceedings of the 14th ACM Conference on Recommender Systems, 230-239, 2020 | 19 | 2020 |
| A deep multi-task approach for residual value forecasting A Rashed, S Jawed, J Rehberg, J Grabocka, L Schmidt-Thieme, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 8 | 2020 |
| Multi-task learning curve forecasting across hyperparameter configurations and datasets S Jawed, H Jomaa, L Schmidt-Thieme, J Grabocka Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 6 | 2021 |
| Data-driven vehicle trajectory forecasting S Jawed, E Boumaiza, J Grabocka, L Schmidt-Thieme arXiv preprint arXiv:1902.05400, 2019 | 6 | 2019 |
| Multi-step forecasting via multi-task learning S Jawed, A Rashed, L Schmidt-Thieme 2019 IEEE International Conference on Big Data (Big Data), 790-799, 2019 | 5 | 2019 |
| Gqformer: A multi-quantile generative transformer for time series forecasting S Jawed, L Schmidt-Thieme 2022 IEEE International Conference on Big Data (Big Data), 992-1001, 2022 | 4 | 2022 |
| GraFITi: Graphs for Forecasting Irregularly Sampled Time Series VK Yalavarthi, K Madhusudhanan, R Scholz, N Ahmed, J Burchert, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16255 …, 2024 | 2 | 2024 |
| FQFormer: A Fully Quantile Transformer for Time Series Forecasting S Jawed, L Schmidt-Thieme 8th SIGKDD International Workshop on Mining and Learning from Time Series …, 2022 | 2 | 2022 |
| Optimal topology search for fast model averaging in decentralized parallel SGD M Jameel, S Jawed, L Schmidt-Thieme Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia …, 2020 | 2 | 2020 |
| Hyperparameter Tuning MLP’s for Probabilistic Time Series Forecasting K Madhusudhanan, S Jawed, L Schmidt-Thieme Pacific-Asia Conference on Knowledge Discovery and Data Mining, 264-275, 2024 | 1 | 2024 |
| Pricing Used Vehicles at Volkswagen Financial Services AG S Jawed, J Stening, L Schmidt-Thieme 2023 IEEE International Conference on Big Data (BigData), 1736-1743, 2023 | 1 | 2023 |
| Forecasting Irregularly Sampled Time Series using Graphs VK Yalavarthi, K Madhusudhanan, R Sholz, N Ahmed, J Burchert, ... arXiv preprint arXiv:2305.12932, 2023 | 1 | 2023 |
| AI and Data-Driven Mobility at Volkswagen Financial Services AG S Jawed, A Rashed, K Madhusudhanan, S Elsayed, M Jameel, A Volk, ... arXiv preprint arXiv:2202.04411, 2022 | 1 | 2022 |
| Forecasting Early with Meta Learning S Jawed, K Madhusudhanan, VK Yalavarthi, L Schmidt-Thieme 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | | 2023 |
| Forecasting Irregularly Sampled Time Series using Graphs V Krishna Yalavarthi, K Madhusudhanan, R Sholz, N Ahmed, J Burchert, ... arXiv e-prints, arXiv: 2305.12932, 2023 | | 2023 |
| Auxiliary Quantile Forecasting with Linear Networks S Jawed, L Schmidt-Thieme arXiv preprint arXiv:2212.02578, 2022 | | 2022 |
Lars Schmidt-ThiemeUniversity of Hildesheim, GermanyVerified email at ismll.uni-hildesheim.de
