| Bayesian nonparametric models. P Orbanz, YW Teh Encyclopedia of machine learning 1, 81-89, 2010 | 327 | 2010 |
| Bayesian models of graphs, arrays and other exchangeable random structures P Orbanz, DM Roy IEEE transactions on pattern analysis and machine intelligence 37 (2), 437-461, 2014 | 313 | 2014 |
| Non-vacuous generalization bounds at the imagenet scale: a PAC-bayesian compression approach W Zhou, V Veitch, M Austern, RP Adams, P Orbanz arXiv preprint arXiv:1804.05862, 2018 | 223 | 2018 |
| Nonparametric Bayesian image segmentation P Orbanz, JM Buhmann International Journal of Computer Vision 77, 25-45, 2008 | 174 | 2008 |
| Cluster analysis of heterogeneous rank data LM Busse, P Orbanz, JM Buhmann Proceedings of the 24th international conference on Machine learning, 113-120, 2007 | 151 | 2007 |
| Random function priors for exchangeable arrays with applications to graphs and relational data J Lloyd, P Orbanz, Z Ghahramani, DM Roy Advances in Neural Information Processing Systems 25, 2012 | 143 | 2012 |
| Distribution theory for hierarchical processes F Camerlenghi, A Lijoi, P Orbanz, I Prünster | 105 | 2019 |
| Dependent Indian buffet processes S Williamson, P Orbanz, Z Ghahramani Proceedings of the thirteenth international conference on artificial …, 2010 | 68 | 2010 |
| Random-walk models of network formation and sequential Monte Carlo methods for graphs B Bloem-Reddy, P Orbanz Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2018 | 44 | 2018 |
| Smooth image segmentation by nonparametric Bayesian inference P Orbanz, JM Buhmann Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz …, 2006 | 41 | 2006 |
| Lecture Notes on Bayesian Nonparametrics P Orbanz | 33 | 2014 |
| Construction of nonparametric Bayesian models from parametric Bayes equations P Orbanz Advances in neural information processing systems 22, 2009 | 33 | 2009 |
| Subsampling large graphs and invariance in networks P Orbanz arXiv preprint arXiv:1710.04217, 2017 | 22 | 2017 |
| Compressibility and generalization in large-scale deep learning W Zhou, V Veitch, M Austern, RP Adams, P Orbanz arXiv preprint arXiv:1804.05862 2, 2018 | 20 | 2018 |
| Limit theorems for distributions invariant under groups of transformations M Austern, P Orbanz The Annals of Statistics 50 (4), 1960-1991, 2022 | 18 | 2022 |
| SAR images as mixtures of Gaussian mixtures P Orbanz, JM Buhmann IEEE International Conference on Image Processing 2005 2, II-209, 2005 | 17 | 2005 |
| Preferential attachment and vertex arrival times B Bloem-Reddy, P Orbanz arXiv preprint arXiv:1710.02159, 2017 | 16 | 2017 |
| Method for operating a hearing device JM Buhmann, S Korl, Y Moh, P Orbanz US Patent 8,477,972, 2013 | 15 | 2013 |
| Projective limit random probabilities on Polish spaces P Orbanz | 14 | 2011 |
| Empirical risk minimization and stochastic gradient descent for relational data V Veitch, M Austern, W Zhou, DM Blei, P Orbanz The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 13 | 2019 |
Joachim M. BuhmannETH ZurichVerified email at inf.ethz.ch
