Vinayak Rao

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Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
David DunsonArts & Sciences Professor of Statistical Science & MathematicsVerified email at duke.edu
Jennifer NevilleMicrosoft Research, Purdue UniversityVerified email at microsoft.com
Bruno RibeiroAssociate Professor of Computer Science at Purdue UniversityVerified email at cs.purdue.edu
Lawrence CarinDuke UniversityVerified email at duke.edu
Balasubramaniam SrinivasanAmazon (AWS)Verified email at amazon.com
Ryan L. MurphyPurdue UniversityVerified email at alumni.purdue.edu
Jiasen YangPurdue UniversityVerified email at purdue.edu
Marc HowardBoston UniversityVerified email at bu.edu
Wenzhao LianGoogle XVerified email at duke.edu
Ricardo HenaoDuke UniversityVerified email at duke.edu
Lizhen LinDepartment of Mathematics, The University of MarylandVerified email at umd.edu
Xin YuanWestlake University, Bell Labs, Duke University, Hong Kong Polytechnic UniversityVerified email at westlake.edu.cn
Boqian ZhangPurdue UniversityVerified email at purdue.edu
Chen ChangyouAssociate Professor at University at BuffaloVerified email at buffalo.edu
Wray BuntineProfessor, VinUniversityVerified email at vinuni.edu.vn
Jiangwei PanNetflixVerified email at netflix.com
Francesca PetraliaIcahn School of Medicine at Mount SinaiVerified email at mssm.edu
Jordan AwanAssistant Professor, Purdue UniversityVerified email at purdue.edu
Shaobo HanNEC Labs America, Duke UniversityVerified email at nec-labs.com

Vinayak Rao

Associate Professor, Department of Statistics, Purdue University

Verified email at purdue.edu - Homepage

Statistics Machine Learning Markov Chain Monte Carlo Bayesian nonparametrics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Relational Pooling for Graph Representations R Murphy, B Srinivasan, V Rao, B Ribeiro International Conference on Machine Learning, 2019	297	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	229	2018
Fast MCMC sampling for Markov jump processes and extensions V Rao, YW Teh The Journal of Machine Learning Research, 2013, 2013	140	2013
Repulsive mixtures F Petralia, V Rao, D Dunson Advances in neural information processing systems 25, 2012	77	2012
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	77	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	71	2015
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	68	2018
Spatial normalized gamma processes V Rao, Y Teh Advances in neural information processing systems 22, 2009	68	2009
Gaussian process modulated renewal processes V Rao, YW Teh Advances in Neural Information Processing Systems, 2474-2482, 2011	63*	2011
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks V Rao, YW Teh arXiv preprint arXiv:1202.3760, 2012	49	2012
Dependent normalized random measures C Chen, V Rao, W Buntine, YW Teh Proceedings of the International Conference on Machine Learning (ICML), 2013	40	2013
Retrieved context and the discovery of semantic structure VA Rao, MW Howard Advances in neural information processing systems 20, 1193, 2008	36	2008
Data augmentation for models based on rejection sampling V Rao, L Lin, DB Dunson Biometrika 103 (2), 319-335, 2016	35	2016
MCMC for continuous-time discrete-state systems V Rao, Y Teh Advances in Neural Information Processing Systems 25, 2012	35	2012
Hierarchical infinite divisibility for multiscale shrinkage X Yuan, V Rao, S Han, L Carin IEEE Transactions on Signal Processing 62 (17), 4363-4374, 2014	31	2014
Bayesian nonparametric inference on the Stiefel manifold L Lin, V Rao, DB Dunson Statistica Sinica 27, 535-553, 2017	27	2017
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	26	2017
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	24	2022
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	21	2016
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	20	2019

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