| pytorch-fid: FID Score for PyTorch M Seitzer | 214 | 2020 |
| Adversarial and perceptual refinement for compressed sensing MRI reconstruction M Seitzer, G Yang, J Schlemper, O Oktay, T Würfl, V Christlein, T Wong, ... Medical Image Computing and Computer Assisted Intervention (MICCAI) 2018 …, 2018 | 129 | 2018 |
| Bridging the gap to real-world object-centric learning M Seitzer, M Horn, A Zadaianchuk, D Zietlow, T Xiao, CJ Simon-Gabriel, ... International Conference on Learning Representations (ICLR) 2023, 2023 | 69 | 2023 |
| On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks M Seitzer, A Tavakoli, D Antic, G Martius International Conference on Learning Representations (ICLR) 2022, 2022 | 64 | 2022 |
| High-fidelity performance metrics for generative models in PyTorch. 2020 A Obukhov, M Seitzer, PW Wu, S Zhydenko, J Kyl, EYJ Lin Version: 0.2. 0, DOI 10, 2020 | 53* | 2020 |
| Causal Influence Detection for Improving Efficiency in Reinforcement Learning M Seitzer, B Schölkopf, G Martius Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021, 2021 | 50 | 2021 |
| Self-supervised Visual Reinforcement Learning with Object-centric Representations A Zadaianchuk, M Seitzer, G Martius International Conference on Learning Representations (ICLR) 2021, 2021 | 25 | 2021 |
| Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities A Zadaianchuk, M Seitzer, G Martius Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023 | 6 | 2023 |
| A bytecode interpreter for secure program execution in untrusted main memory M Seitzer, M Gruhn, T Müller Computer Security--ESORICS 2015: 20th European Symposium on Research in …, 2015 | 4 | 2015 |
| DyST: Towards Dynamic Neural Scene Representations on Real-World Videos M Seitzer, S van Steenkiste, T Kipf, K Greff, MSM Sajjadi International Conference on Learning Representations (ICLR) 2024, 2023 | 1 | 2023 |
| NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Learned Aggregation of Convolutional Feature Maps M Seitzer, A Foltyn, FP Kemeth arXiv preprint arXiv:2002.12356, 2020 | | 2020 |
| NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Aggregated Convolutional Feature Maps M Seitzer arXiv preprint arXiv:2002.10003, 2020 | | 2020 |
Georg MartiusUniversity of Tübingen and Max Planck Institute for Intelligent SystemsBestätigte E-Mail-Adresse bei uni-tuebingen.de
