37 citations · 38 across the 4 of their papers we have counts for
11 papers
Contextual Unsupervised Outlier Detection in Sequences
Mohamed A. Zahran, Leonardo Teixeira, Vinayak Rao +1
This work proposes an unsupervised learning framework for trajectory (sequence) outlier detection that combines ranking tests with user sequence models. The overall framework ident…
Variational Bayesian Methods for Stochastically Constrained System Design Problems
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
We study system design problems stated as parameterized stochastic programs with a chance-constraint set. We adopt a Bayesian approach that requires the computation of a posterior…
Asymptotic Consistency of Loss-Calibrated Variational Bayes
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
This paper establishes the asymptotic consistency of the {\it loss-calibrated variational Bayes} (LCVB) method. LCVB was proposed in~\cite{LaSiGh2011} as a method for approximately…
Community detection over a heterogeneous population of non-aligned networks
Guilherme Gomes, Vinayak Rao, Jennifer Neville
Clustering and community detection with multiple graphs have typically focused on aligned graphs, where there is a mapping between nodes across the graphs (e.g., multi-view, multi-…
An Exact Auxiliary Variable Gibbs Sampler for a Class of Diffusions
Qi Wang, Vinayak Rao, Yee Whye Teh
Stochastic differential equations (SDEs) or diffusions are continuous-valued continuous-time stochastic processes widely used in the applied and mathematical sciences. Simulating p…
Relational Pooling for Graph Representations
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak Rao +1
This work generalizes graph neural networks (GNNs) beyond those based on the Weisfeiler-Lehman (WL) algorithm, graph Laplacians, and diffusions. Our approach, denoted Relational Po…