| Yformer: U-net inspired transformer architecture for far horizon time series forecasting K Madhusudhanan, J Burchert, N Duong-Trung, S Born, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2023 | 29* | 2023 |
| Multimodal meta-learning for time series regression SP Arango, F Heinrich, K Madhusudhanan, L Schmidt-Thieme Advanced Analytics and Learning on Temporal Data: 6th ECML PKDD Workshop …, 2021 | 15 | 2021 |
| Put attention to temporal saliency patterns of multi-horizon time series N Duong-Trung, S Born, K Madhusudhanan, R Scholz, J Burchert, ... arXiv preprint arXiv 2212, 2022 | 2 | 2022 |
| 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 |
| 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 | 1 | 2024 |
| 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 |
| Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting VK Yalavarthi, R Scholz, K Madhusudhanan, S Born, L Schmidt-Thieme arXiv preprint arXiv:2406.07246, 2024 | | 2024 |
| Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting V Krishna Yalavarthi, R Scholz, K Madhusudhanan, S Born, ... arXiv e-prints, arXiv: 2406.07246, 2024 | | 2024 |
| ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing K Madhusudhanan, G Behrens, M Stubbemann, L Schmidt-Thieme arXiv preprint arXiv:2403.03812, 2024 | | 2024 |
| Predicting Deviation of Flight Entry into Air Sector using Machine Learning Techniques C Klötergens, C Acevedo, I Firmansyah, L Antiqui, K Madhusudhanan, ... 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), 1-10, 2023 | | 2023 |
| 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 |
| 3D object reconstruction from a single 2D image: performance of two novel frameworks based on lightweight CNN architectures and free-form deformation of meshes S Pradhan, K Madhusudhanan, L Munoz-Giraldo, MU Faruq, H Jomaa Eleventh International Conference on Graphics and Image Processing (ICGIP …, 2020 | | 2020 |
Lars Schmidt-ThiemeUniversity of Hildesheim, GermanyVerified email at ismll.uni-hildesheim.de
