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Vinayak Rao
Vinayak Rao
Associate Professor, Department of Statistics, Purdue University
Verified email at purdue.edu - Homepage
Title
Cited by
Cited by
Year
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
1442018
Relational Pooling for Graph Representations
R Murphy, B Srinivasan, V Rao, B Ribeiro
International Conference on Machine Learning, 2019
1432019
Fast MCMC sampling for Markov jump processes and extensions
V Rao, YW Teh
The Journal of Machine Learning Research, 2013, 2013
1282013
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
612009
Spatial normalized gamma processes
V Rao, Y Teh
Advances in neural information processing systems 22, 2009
612009
A multitask point process predictive model
W Lian, R Henao, V Rao, J Lucas, L Carin
International Conference on Machine Learning, 2030-2038, 2015
582015
Gaussian process modulated renewal processes
V Rao, YW Teh
Advances in Neural Information Processing Systems, 2474-2482, 2011
57*2011
Repulsive mixtures
F Petralia, V Rao, D Dunson
Advances in neural information processing systems 25, 2012
532012
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
V Rao, YW Teh
arXiv preprint arXiv:1202.3760, 2012
492012
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
412018
Dependent normalized random measures
C Chen, V Rao, W Buntine, YW Teh
International Conference on Machine Learning, 969-977, 2013
382013
Dependent normalized random measures
C Chen, V Rao, W Buntine, YW Teh
Proceedings of the International Conference on Machine Learning (ICML), 2013
382013
MCMC for continuous-time discrete-state systems
V Rao, Y Teh
Advances in Neural Information Processing Systems 25, 2012
342012
Hierarchical infinite divisibility for multiscale shrinkage
X Yuan, V Rao, S Han, L Carin
IEEE Transactions on Signal Processing 62 (17), 4363-4374, 2014
302014
Retrieved context and the discovery of semantic structure
VA Rao, MW Howard
Advances in neural information processing systems 20, 1193, 2008
302008
Data augmentation for models based on rejection sampling
V Rao, L Lin, DB Dunson
Biometrika 103 (2), 319-335, 2016
252016
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
182017
Bayesian nonparametric inference on the Stiefel manifold
L Lin, V Rao, DB Dunson
Statistica Sinica 27, 535-553, 2017
172017
Markov-modulated Marked Poisson Processes for Check-in Data
J Pan, V Rao, PK Agarwal, AE Gelfand
Proceedings of The 33rd International Conference on Machine Learning, 2016
172016
Modeling correlated arrival events with latent semi-markov processes
W Lian, V Rao, B Eriksson, L Carin
International Conference on Machine Learning, 396-404, 2014
172014
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