| Yformer: U-net inspired transformer architecture for far horizon time series forecasting K Madhusudhanan, J Burchert, N Duong-Trung, S Born, ... arXiv preprint arXiv:2110.08255, 2021 | 18 | 2021 |
| U-net inspired transformer architecture for far horizon time series forecasting K Madhusudhanan, J Burchert, N Duong-Trung, S Born, ... Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 11 | 2022 |
| Few-shot forecasting of time-series with heterogeneous channels L Brinkmeyer, RR Drumond, J Burchert, L Schmidt-Thieme Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 8 | 2022 |
| DCSF: deep convolutional set functions for classification of asynchronous time series VK Yalavarthi, J Burchert, L Schmidt-Thieme 2022 IEEE 9th International Conference on Data Science and Advanced …, 2022 | 5 | 2022 |
| Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series VK Yalavarthi, J Burchert, L Schmidt-Thieme 2023 IEEE International Conference on Big Data (BigData), 986-995, 2023 | 2 | 2023 |
| 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 |
| Tripletformer for Probabilistic Interpolation of Asynchronous Time Series VK Yalavarthi, J Burchert, L Schmidt-Thieme arXiv preprint arXiv:2210.02091, 2022 | 2 | 2022 |
| Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training J Burchert, T Werner, VK Yalavarthi, DC de Portugal, M Stubbemann, ... arXiv preprint arXiv:2404.06966, 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 |
| Towards Comparable Active Learning T Werner, J Burchert, L Schmidt-Thieme arXiv preprint arXiv:2311.18356, 2023 | | 2023 |
| GraFITi: Forecasting Irregularly Sampled Time Series using Graphs VK Yalavarthi, K Madusudanan, R Sholz, N Ahmed, J Burchert, S Javed, ... arXiv preprint arXiv:2305.12932, 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 |
| ConvMix: Combining Intermediate Latent Features in Deep Convolutional Neural Networks MI Arif, J Burchert, L Schmidt-Thieme Scandinavian Conference on Image Analysis, 156-174, 2023 | | 2023 |
| Tripletformer for Probabilistic Interpolation of Asynchronous Time Series V Krishna Yalavarthi, J Burchert, L Schmidt-thieme arXiv e-prints, arXiv: 2210.02091, 2022 | | 2022 |
| DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series V Krishna Yalavarthi, J Burchert, L Schmidt-Thieme arXiv e-prints, arXiv: 2208.11374, 2022 | | 2022 |
