Assistant Professor
News
05/2018: Papers accepted at ICML and UAI
02/2018: Paper accepted at AISTATS with Xi Tan and Jennifer Neville: "Nested CRP with Hawkes-Gaussian Processes"
09/2017: Paper accepted at NIPS with Jiangwei Pan and Boqian Zhang: "Collapsed variational inference for Markov jump processes"
06/2017: Paper accepted at UAI with Jiasen Yang and Jennifer Neville: "Decoupling Homophily and Reciprocity with Latent Space Network Models"
04/2017: New paper on arxiv with Boqian Zhang: "Efficient MCMC for parameter inference for Markov jump processes."
06/2016: "Bayesian inference for Matérn repulsive processes accepted at JRSS-B."
05/2016: "Papers accepted at the International Conf. on Machine Learning and Uncertainty in Artificial Intelligence."
01/2016: "Data augmentation for models based on rejection sampling" accepted at Biometrika.
01/2016: "Bayesian nonparametric inference on the Stiefel manifold" is accepted at Statistica Sinica.
02/2018: Paper accepted at AISTATS with Xi Tan and Jennifer Neville: "Nested CRP with Hawkes-Gaussian Processes"
09/2017: Paper accepted at NIPS with Jiangwei Pan and Boqian Zhang: "Collapsed variational inference for Markov jump processes"
06/2017: Paper accepted at UAI with Jiasen Yang and Jennifer Neville: "Decoupling Homophily and Reciprocity with Latent Space Network Models"
04/2017: New paper on arxiv with Boqian Zhang: "Efficient MCMC for parameter inference for Markov jump processes."
06/2016: "Bayesian inference for Matérn repulsive processes accepted at JRSS-B."
05/2016: "Papers accepted at the International Conf. on Machine Learning and Uncertainty in Artificial Intelligence."
01/2016: "Data augmentation for models based on rejection sampling" accepted at Biometrika.
01/2016: "Bayesian nonparametric inference on the Stiefel manifold" is accepted at Statistica Sinica.
Contact
MATH 212
150 N University St,
Purdue Univ.
West Lafayette, IN 47907
Phone: 765-494-3956
Fax: 765-494-0058
varao (at) purdue.edu
google scholar
flickr
Research Interests:
- Bayesian nonparametrics:
Dependent nonparametric models, MCMC methods and deterministic approximations for efficient inference in nonparametric models - Continuous time stochastic processes:
MCMC methods for inference in Markov jump processes and continuous time Bayesian networks - Point processes:
Nonstationary renewal processes and repulsive point processes - Markov chain Monte Carlo for doubly intractable problems
- Machine learning
Selected publications:
- Zhang, B. and Rao, V.A. (2018)
Efficient parameter sampling for Markov jump processes
[arxiv:1704.02369]
- Rao, V.A., Adams,R.P. and Dunson, D.B. (2016)
Bayesian inference for Matérn repulsive processes
(accepted at JRSS-B)
[arxiv:1308.1136] [supplementary] [bibtex]
- Rao, V.A., Lin, L. and Dunson, D.B. (2016)
Data augmentation for models based on rejection sampling
Biometrika
[Biometrika] [bibtex]
- Rao,V.A. and Teh, Y.W. (2013)
Fast MCMC sampling for Markov jump processes and extensions
Journal of Machine Learning Research 14:3295−3320, 2013
[pdf] [JMLR] [bibtex]
- Rao,V.A. and Teh, Y.W. (2009)
Spatial normalized Gamma processes
Advances in Neural Information Processing Systems 22 (NIPS 2009)
[pdf] [bibtex]