| Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks M Lienen, S Günnemann International Conference on Learning Representations, 2022 | 47 | 2022 |
| From Zero to Turbulence: Generative Modeling for 3D Flow Simulation M Lienen, D Lüdke, J Hansen-Palmus, S Günnemann International Conference on Learning Representations, 2024 | 35* | 2024 |
| FLGR: Fixed length gists representation learning for RNN-HMM hybrid-based neuromorphic continuous gesture recognition G Chen, J Chen, M Lienen, J Conradt, F Röhrbein, AC Knoll Frontiers in Neuroscience, 73, 2019 | 15 | 2019 |
| Scalable optimal transport in high dimensions for graph distances, embedding alignment, and more J Gasteiger, M Lienen, S Günnemann International Conference on Machine Learning, 5616-5627, 2021 | 14 | 2021 |
| Add and thin: Diffusion for temporal point processes D Lüdke, M Biloš, O Shchur, M Lienen, S Günnemann Advances in Neural Information Processing Systems 36, 2024 | 12 | 2024 |
| torchode: A parallel ODE solver for pytorch M Lienen, S Günnemann arXiv preprint arXiv:2210.12375, 2022 | 11 | 2022 |
| Assessing robustness via score-based adversarial image generation M Kollovieh, L Gosch, Y Scholten, M Lienen, S Günnemann arXiv preprint arXiv:2310.04285, 2023 | 4 | 2023 |
| Unfolding Time: Generative Modeling for Turbulent Flows in 4D A Saydemir, M Lienen, S Günnemann arXiv preprint arXiv:2406.11390, 2024 | 2 | 2024 |
| Rate-adaptive Link Quality Estimation for Coded Packet Networks M Leclaire, SM Günther, M Lienen, M Riemensberger, G Carle 2016 IEEE 41st Conference on Local Computer Networks (LCN), 732-740, 2016 | 2 | 2016 |
| Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting M Kollovieh, M Lienen, D Lüdke, L Schwinn, S Günnemann arXiv preprint arXiv:2410.03024, 2024 | 1 | 2024 |
| Scalable emulation of protein equilibrium ensembles with generative deep learning S Lewis, T Hempel, J Jiménez Luna, M Gastegger, Y Xie, AYK Foong, ... bioRxiv, 2024.12. 05.626885, 2024 | 1 | 2024 |
| Generative Modeling with Bayesian Sample Inference M Lienen, M Kollovieh, S Günnemann arXiv preprint arXiv:2502.07580, 2025 | | 2025 |
Stephan GünnemannProfessor of Computer Science, Technical University of MunichΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα in.tum.de
