| f-gan: Training generative neural samplers using variational divergence minimization S Nowozin, B Cseke, R Tomioka Advances in neural information processing systems 29, 2016 | 1402 | 2016 |
| 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 | 1313 | 2019 |
| On feature combination for multiclass object classification P Gehler, S Nowozin 2009 IEEE 12th International Conference on Computer Vision, 221-228, 2009 | 1073 | 2009 |
| Which training methods for GANs do actually converge? L Mescheder, A Geiger, S Nowozin International conference on machine learning, 3481-3490, 2018 | 996 | 2018 |
| 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 | 938 | 2019 |
| Optimization for machine learning S Sra, S Nowozin, SJ Wright Mit Press, 2012 | 770 | 2012 |
| 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 | 656 | 2017 |
| 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 | 529 | 2016 |
| Deepcoder: Learning to write programs M Balog, AL Gaunt, M Brockschmidt, S Nowozin, D Tarlow arXiv preprint arXiv:1611.01989, 2016 | 528 | 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 | 501 | 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 | 478 | 2012 |
| 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 | 445 | 2017 |
| 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 | 433 | 2011 |
| The numerics of gans L Mescheder, S Nowozin, A Geiger Advances in neural information processing systems 30, 2017 | 400 | 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 | 398 | 2017 |
| Discriminative subsequence mining for action classification S Nowozin, G Bakir, K Tsuda 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007 | 257 | 2007 |
| 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 | 251 | 2018 |
| A comparative study of modern inference techniques for structured discrete energy minimization problems JH Kappes, B Andres, FA Hamprecht, C Schnörr, S Nowozin, D Batra, ... International Journal of Computer Vision 115 (2), 155-184, 2015 | 216 | 2015 |
| A comparative study of modern inference techniques for discrete energy minimization problems J Kappes, B Andres, F Hamprecht, C Schnorr, S Nowozin, D Batra, S Kim, ... Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 213 | 2013 |
| 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 | 202 | 2020 |
Peter GehlerAmazonVerified email at amazon.com
