| Occupancy networks: Learning 3d reconstruction in function space L Mescheder, M Oechsle, M Niemeyer, S Nowozin, A Geiger Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 3812 | 2019 |
| Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, J Dillon, ... Advances in neural information processing systems 32, 2019 | 2454 | 2019 |
| f-gan: Training generative neural samplers using variational divergence minimization S Nowozin, B Cseke, R Tomioka Advances in neural information processing systems 29, 2016 | 2214 | 2016 |
| Which training methods for GANs do actually converge? L Mescheder, A Geiger, S Nowozin International conference on machine learning, 3481-3490, 2018 | 1984 | 2018 |
| Optimization for machine learning S Sra, S Nowozin, SJ Wright MIT press, 2011 | 1132 | 2011 |
| On feature combination for multiclass object classification P Gehler, S Nowozin 2009 IEEE 12th International Conference on Computer Vision, 221-228, 2009 | 1115 | 2009 |
| Pixeldefend: Leveraging generative models to understand and defend against adversarial examples Y Song, T Kim, S Nowozin, S Ermon, N Kushman arXiv preprint arXiv:1710.10766, 2017 | 1074 | 2017 |
| Dsac-differentiable ransac for camera localization E Brachmann, A Krull, S Nowozin, J Shotton, F Michel, S Gumhold, ... Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 820 | 2017 |
| Deepcoder: Learning to write programs M Balog, AL Gaunt, M Brockschmidt, S Nowozin, D Tarlow arXiv preprint arXiv:1611.01989, 2016 | 805 | 2016 |
| Oblivious {Multi-Party} machine learning on trusted processors O Ohrimenko, F Schuster, C Fournet, A Mehta, S Nowozin, K Vaswani, ... 25th USENIX Security Symposium (USENIX Security 16), 619-636, 2016 | 742 | 2016 |
| Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks L Mescheder, S Nowozin, A Geiger International conference on machine learning, 2391-2400, 2017 | 725 | 2017 |
| Stabilizing training of generative adversarial networks through regularization K Roth, A Lucchi, S Nowozin, T Hofmann Advances in neural information processing systems 30, 2017 | 589 | 2017 |
| The numerics of gans L Mescheder, S Nowozin, A Geiger Advances in neural information processing systems 30, 2017 | 556 | 2017 |
| Instructing people for training gestural interactive systems S Fothergill, H Mentis, P Kohli, S Nowozin Proceedings of the SIGCHI conference on human factors in computing systems …, 2012 | 536 | 2012 |
| Structured learning and prediction in computer vision S Nowozin, CH Lampert Foundations and trends in computer graphics and vision 6 (3-4), 185-365, 2011 | 524 | 2011 |
| How good is the bayes posterior in deep neural networks really? F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ... arXiv preprint arXiv:2002.02405, 2020 | 489 | 2020 |
| Multi-level variational autoencoder: Learning disentangled representations from grouped observations D Bouchacourt, R Tomioka, S Nowozin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 399 | 2018 |
| Meta-learning probabilistic inference for prediction J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner arXiv preprint arXiv:1805.09921, 2018 | 359 | 2018 |
| Fast and flexible multi-task classification using conditional neural adaptive processes J Requeima, J Gordon, J Bronskill, S Nowozin, RE Turner Advances in neural information processing systems 32, 2019 | 330 | 2019 |
| Deterministic variational inference for robust bayesian neural networks A Wu, S Nowozin, E Meeds, RE Turner, JM Hernandez-Lobato, AL Gaunt arXiv preprint arXiv:1810.03958, 2018 | 275 | 2018 |
Peter GehlerTübingen AI Center, University TübingenVerified email at uni-tuebingen.de
