Vinayak A. Rao

Publication Activity (10 Years)

Years Active: 2007-2023
Publications (10 Years): 28

Top Topics

Graph Representations

Variational Bayes

Top Venues

Publications

Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
Bayesian Joint Chance Constrained Optimization: Approximations and Statistical Consistency. SIAM J. Optim. 33 (3) (2023)
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making. NeurIPS (2023)
Imon Banerjee, Harsha Honnappa, Vinayak A. Rao
Offline Estimation of Controlled Markov Chains: Minimax Nonparametric Estimators and Sample Efficiency. CoRR (2022)
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
Bayesian Joint Chance Constrained Optimization: Approximations and Statistical Consistency. CoRR (2021)
Imon Banerjee, Vinayak A. Rao, Harsha Honnappa
PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models. Entropy 23 (3) (2021)
Yangze Zhou, Vinayak A. Rao, Bruno Ribeiro
Set Twister for Single-hop Node Classification. CoRR (2021)
Mohamed A. Zahran, Leonardo Teixeira, Vinayak A. Rao, Bruno Ribeiro
Contextual Unsupervised Outlier Detection in Sequences. CoRR (2021)
Prateek Jaiswal, Vinayak A. Rao, Harsha Honnappa
Asymptotic Consistency of α-Rényi-Approximate Posteriors. J. Mach. Learn. Res. 21 (2020)
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
Variational Bayesian Methods for Stochastically Constrained System Design Problems. CoRR (2020)
Guilherme Gomes, Vinayak A. Rao, Jennifer Neville
Community detection over a heterogeneous population of non-aligned networks. CoRR (2019)
Prateek Jaiswal, Vinayak A. Rao, Harsha Honnappa
Asymptotic Consistency of $α-$Rényi-Approximate Posteriors. CoRR (2019)
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
Asymptotic Consistency of Loss-Calibrated Variational Bayes. CoRR (2019)
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak A. Rao, Bruno Ribeiro
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs. ICLR (Poster) (2019)
Jiasen Yang, Vinayak A. Rao, Jennifer Neville
A Stein-Papangelou Goodness-of-Fit Test for Point Processes. AISTATS (2019)
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak A. Rao, Bruno Ribeiro
Relational Pooling for Graph Representations. ICML (2019)
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
Variational Bayesian Methods for Stochastically Constrained System Design Problems. AABI (2019)
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak A. Rao, Bruno Ribeiro
Relational Pooling for Graph Representations. CoRR (2019)
Guilherme Gomes, Vinayak A. Rao, Jennifer Neville
Multi-level hypothesis testing for populations of heterogeneous networks. CoRR (2018)
Guilherme Gomes, Vinayak A. Rao, Jennifer Neville
Multi-level Hypothesis Testing for Populations of Heterogeneous Networks. ICDM (2018)
Xi Tan, Vinayak A. Rao, Jennifer Neville
Nested CRP with Hawkes-Gaussian Processes. AISTATS (2018)
Xi Tan, Vinayak A. Rao, Jennifer Neville
The Indian Buffet Hawkes Process to Model Evolving Latent Influences. UAI (2018)
Jiasen Yang, Qiang Liu, Vinayak A. Rao, Jennifer Neville
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy. ICML (2018)
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak A. Rao, Bruno Ribeiro
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs. CoRR (2018)
Jiasen Yang, Vinayak A. Rao, Jennifer Neville
Decoupling Homophily and Reciprocity with Latent Space Network Models. UAI (2017)
Boqian Zhang, Jiangwei Pan, Vinayak A. Rao
Collapsed variational Bayes for Markov jump processes. NIPS (2017)
Jiangwei Pan, Vinayak A. Rao, Pankaj K. Agarwal, Alan E. Gelfand
Markov-modulated Marked Poisson Processes for Check-in Data. ICML (2016)
Xi Tan, Syed A. Z. Naqvi, Yuan (Alan) Qi, Katherine A. Heller, Vinayak A. Rao
Content-based Modeling of Reciprocal Relationships using Hawkes and Gaussian Processes. UAI (2016)
Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin
A Multitask Point Process Predictive Model. ICML (2015)
Wenzhao Lian, Vinayak A. Rao, Brian Eriksson, Lawrence Carin
Modeling Correlated Arrival Events with Latent Semi-Markov Processes. ICML (2014)
Xin Yuan, Vinayak A. Rao, Shaobo Han, Lawrence Carin
Hierarchical Infinite Divisibility for Multiscale Shrinkage. IEEE Trans. Signal Process. 62 (17) (2014)
Changyou Chen, Vinayak A. Rao, Wray L. Buntine, Yee Whye Teh
Dependent Normalized Random Measures. ICML (3) (2013)
Vinayak A. Rao, Yee Whye Teh
Fast MCMC sampling for Markov jump processes and extensions. J. Mach. Learn. Res. 14 (1) (2013)
David E. Carlson, Vinayak A. Rao, Joshua T. Vogelstein, Lawrence Carin
Real-Time Inference for a Gamma Process Model of Neural Spiking. NIPS (2013)
Vinayak A. Rao, Yee Whye Teh
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks CoRR (2012)
Francesca Petralia, Vinayak A. Rao, David B. Dunson
Repulsive Mixtures. NIPS (2012)
Vinayak A. Rao, Yee Whye Teh
MCMC for continuous-time discrete-state systems. NIPS (2012)
Vinayak A. Rao, Yee Whye Teh
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks. UAI (2011)
Vinayak A. Rao, Yee Whye Teh
Gaussian process modulated renewal processes. NIPS (2011)
Vinayak A. Rao, Yee Whye Teh
Spatial Normalized Gamma Processes. NIPS (2009)
Vinayak A. Rao, Marc W. Howard
Retrieved context and the discovery of semantic structure. NIPS (2007)