| Relational Pooling for Graph Representations R Murphy, B Srinivasan, V Rao, B Ribeiro International Conference on Machine Learning, 2019 | 354 | 2019 |
| Janossy pooling: Learning deep permutation-invariant functions for variable-size inputs RL Murphy, B Srinivasan, V Rao, B Ribeiro International Conference on Learning Representations, 2018 | 268 | 2018 |
| Fast MCMC sampling for Markov jump processes and extensions V Rao, YW Teh The Journal of Machine Learning Research, 2013, 2013 | 149 | 2013 |
| Repulsive mixtures F Petralia, V Rao, D Dunson Advances in neural information processing systems 25, 2012 | 89 | 2012 |
| Goodness-of-fit testing for discrete distributions via Stein discrepancy J Yang, Q Liu, V Rao, J Neville International Conference on Machine Learning, 5561-5570, 2018 | 82 | 2018 |
| Bridging the gap: transitive associations between items presented in similar temporal contexts. MW Howard, B Jing, VA Rao, JP Provyn, AV Datey Journal of Experimental Psychology: Learning, Memory, and Cognition 35 (2), 391, 2009 | 81 | 2009 |
| A multitask point process predictive model W Lian, R Henao, V Rao, J Lucas, L Carin International conference on machine learning, 2030-2038, 2015 | 75 | 2015 |
| Spatial normalized gamma processes V Rao, Y Teh Advances in neural information processing systems 22, 2009 | 70 | 2009 |
| Gaussian process modulated renewal processes V Rao, YW Teh Advances in Neural Information Processing Systems, 2474-2482, 2011 | 64* | 2011 |
| Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks V Rao, YW Teh arXiv preprint arXiv:1202.3760, 2012 | 52 | 2012 |
| Hanyu fangyan dituji [Linguistic atlas of Chinese dialects] Z Cao Shangwu yinshuguan, 2008 | 48 | 2008 |
| Data augmentation for models based on rejection sampling V Rao, L Lin, DB Dunson Biometrika 103 (2), 319-335, 2016 | 42 | 2016 |
| Dependent normalized random measures C Chen, V Rao, W Buntine, YW Teh Proceedings of the International Conference on Machine Learning (ICML), 2013 | 42 | 2013 |
| Data augmentation MCMC for Bayesian inference from privatized data N Ju, J Awan, R Gong, V Rao Advances in neural information processing systems 35, 12732-12743, 2022 | 40 | 2022 |
| MCMC for continuous-time discrete-state systems V Rao, Y Teh Advances in Neural Information Processing Systems 25, 2012 | 36 | 2012 |
| Retrieved context and the discovery of semantic structure VA Rao, MW Howard Advances in neural information processing systems 20, 1193, 2008 | 36 | 2008 |
| Bayesian nonparametric inference on the Stiefel manifold L Lin, V Rao, DB Dunson Statistica Sinica 27, 535-553, 2017 | 31 | 2017 |
| Hierarchical infinite divisibility for multiscale shrinkage X Yuan, V Rao, S Han, L Carin IEEE Transactions on Signal Processing 62 (17), 4363-4374, 2014 | 30 | 2014 |
| Decoupling Homophily and Reciprocity with Latent Space Network Models J Yang, V Rao, J Neville Proceedings of The 33rd Conference on Uncertainty in Artificial Intelligence …, 2017 | 28 | 2017 |
| A Stein–Papangelou Goodness-of-Fit Test for Point Processes J Yang, V Rao, J Neville International Conference on Artificial Intelligence and Statistics (AISTATS), 2019 | 26 | 2019 |
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Director, Google DeepMindVerified email at stats.ox.ac.uk
