activity
20162022
most citedImpact of Geographic Diversity on Citation of Collaborative Research

3 citations · 5 across the 2 of their papers we have counts for

collaborators

6 papers

cs.DL2022★ 3 cited

Impact of Geographic Diversity on Citation of Collaborative Research

Cian Naik, Cassidy R. Sugimoto, Vincent Larivière +2

Diversity in human capital is widely seen as critical to creating holistic and high quality research, especially in areas that engage with diverse cultures, environments, and chall…

stat.ML2022★ 2 cited

Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement

Cian Naik, Judith Rousseau, Trevor Campbell

Bayesian coresets approximate a posterior distribution by building a small weighted subset of the data points. Any inference procedure that is too computationally expensive to be r…

stat.ME2019

Sparse Networks with Core-Periphery Structure

Cian Naik, François Caron, Judith Rousseau

We propose a statistical model for graphs with a core-periphery structure. To do this we define a precise notion of what it means for a graph to have this structure, based on the s…

stat.AP2017

Quantifying the causal effect of speed cameras on road traffic accidents via an approximate Bayesian doubly robust estimator

Daniel J Graham, Cian Naik, Emma J McCoy +1

This paper quantifies the effect of speed cameras on road traffic collisions using an approximate Bayesian doubly-robust (DR) causal inference estimation method. Previous empirical…

stat.ME2016

Multiply robust dose-response estimation for multivalued causal inference problems

Cian Naik, Emma J. McCoy, Daniel J. Graham

This paper develops a multiply robust (MR) dose-response estimator for causal inference problems involving multivalued treatments. We combine a family of generalised propensity sco…

stat.ML2016

Bayesian Nonparametrics for Sparse Dynamic Networks

Cian Naik, Francois Caron, Judith Rousseau +2

In this paper we propose a Bayesian nonparametric approach to modelling sparse time-varying networks. A positive parameter is associated to each node of a network, which models the…