| Efficient decentralized deep learning by dynamic model averaging M Kamp, L Adilova, J Sicking, F Hüger, P Schlicht, T Wirtz, S Wrobel Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 167 | 2019 |
| Inspect, understand, overcome: A survey of practical methods for ai safety S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ... Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 74 | 2022 |
| Distribution of the smallest eigenvalue in the correlated Wishart model T Wirtz, T Guhr Physical review letters 111 (9), 094101, 2013 | 32 | 2013 |
| Completing the picture for the smallest eigenvalue of real Wishart matrices G Akemann, T Guhr, M Kieburg, R Wegner, T Wirtz Physical Review Letters 113 (25), 250201, 2014 | 22 | 2014 |
| Research on layer manufacturing techniques at Fraunhofer C Ader, M Brosemer, C Freyer, H Fricke, D Hennigs, F Klocke, V Kühne, ... | 21 | 2004 |
| Distribution of the smallest eigenvalue in complex and real correlated Wishart ensembles T Wirtz, T Guhr Journal of Physics A: Mathematical and Theoretical 47 (7), 075004, 2014 | 17 | 2014 |
| Eigenvalue density of the doubly correlated Wishart model: exact results D Waltner, T Wirtz, T Guhr Journal of Physics A: Mathematical and Theoretical 48 (17), 175204, 2015 | 15 | 2015 |
| The smallest eigenvalue distribution in the real Wishart–Laguerre ensemble with even topology T Wirtz, G Akemann, T Guhr, M Kieburg, R Wegner Journal of Physics A: Mathematical and Theoretical 48 (24), 245202, 2015 | 14 | 2015 |
| Worldsheet operator product expansions and p-point functions in AdS3/CFT2 I Kirsch, T Wirtz Journal of High Energy Physics 2011 (10), 1-20, 2011 | 13 | 2011 |
| Limiting statistics of the largest and smallest eigenvalues in the correlated Wishart model T Wirtz, M Kieburg, T Guhr Europhysics Letters 109 (2), 20005, 2015 | 11 | 2015 |
| The correlated Jacobi and the correlated Cauchy–Lorentz ensembles T Wirtz, D Waltner, M Kieburg, S Kumar Journal of Statistical Physics 162, 495-521, 2016 | 10 | 2016 |
| Street-map based validation of semantic segmentation in autonomous driving L von Rueden, T Wirtz, F Hueger, JD Schneider, N Piatkowski, ... 2020 25th International Conference on Pattern Recognition (ICPR), 10203-10210, 2021 | 9 | 2021 |
| Characteristics of Monte Carlo dropout in wide neural networks J Sicking, M Akila, T Wirtz, S Houben, A Fischer arXiv preprint arXiv:2007.05434, 2020 | 9 | 2020 |
| Supporting verification of news articles with automated search for semantically similar articles V Gupta, K Beckh, S Giesselbach, D Wegener, T Wirtz arXiv preprint arXiv:2103.15581, 2021 | 7 | 2021 |
| A novel regression loss for non-parametric uncertainty optimization J Sicking, M Akila, M Pintz, T Wirtz, A Fischer, S Wrobel arXiv preprint arXiv:2101.02726, 2021 | 6 | 2021 |
| Validation of simulation-based testing: Bypassing domain shift with label-to-image synthesis J Rosenzweig, E Brito, HU Kobialka, M Akila, NM Schmidt, P Schlicht, ... 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 182-189, 2021 | 5 | 2021 |
| Wasserstein dropout J Sicking, M Akila, M Pintz, T Wirtz, S Wrobel, A Fischer Machine Learning 113 (5), 3161-3204, 2024 | 4 | 2024 |
| Multi-agent neural rewriter for vehicle routing with limited disclosure of costs N Paul, T Wirtz, S Wrobel, A Kister arXiv preprint arXiv:2206.05990, 2022 | 4 | 2022 |
| Approaching neural network uncertainty realism J Sicking, A Kister, M Fahrland, S Eickeler, F Hüger, S Rüping, P Schlicht, ... arXiv preprint arXiv:2101.02974, 2021 | 3 | 2021 |
| DenseHMM: Learning hidden markov models by learning dense representations J Sicking, M Pintz, M Akila, T Wirtz arXiv preprint arXiv:2012.09783, 2020 | 3 | 2020 |
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