Vinayak Rao
Vinayak Rao
Associate Professor, Department of Statistics, Purdue University
purdue.edu의 이메일 확인됨 - 홈페이지
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Fast MCMC sampling for Markov jump processes and extensions
V Rao, YW Teh
The Journal of Machine Learning Research, 2013, 2013
1212013
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
952018
Relational Pooling for Graph Representations
R Murphy, B Srinivasan, V Rao, B Ribeiro
International Conference on Machine Learning, 2019
842019
Spatial normalized gamma processes
V Rao, Y Teh
Advances in neural information processing systems 22, 1554-1562, 2009
672009
A multitask point process predictive model
W Lian, R Henao, V Rao, J Lucas, L Carin
International Conference on Machine Learning, 2030-2038, 2015
562015
Gaussian process modulated renewal processes
V Rao, YW Teh
Advances in Neural Information Processing Systems, 2474-2482, 2011
552011
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
532009
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
V Rao, YW Teh
arXiv preprint arXiv:1202.3760, 2012
522012
Repulsive mixtures
F Petralia, V Rao, DB Dunson
arXiv preprint arXiv:1204.5243, 2012
452012
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.
VA Rao, YW Teh
NIPS 12, 701-709, 2012
342012
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
312018
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
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
Data augmentation for models based on rejection sampling
V Rao, L Lin, DB Dunson
Biometrika 103 (2), 319-335, 2016
162016
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
162016
Bayesian inference for Matérn repulsive processes
V Rao, RP Adams, DD Dunson
Series B Statistical methodology, 2017
122017
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
122017
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