60 citations · 131 across the 12 of their papers we have counts for
7 papers · 1 filter
Dynamic causal inference with time series data
Tanique Schaffe-Odeleye, Kōsaku Takanashi, Vishesh Karwa +2
We generalize the potential outcome framework to time series with an intervention by defining causal effects on stochastic processes. Interventions in dynamic systems alter not onl…
Non-asymptotic goodness-of-fit tests and model selection in valued stochastic blockmodels
Félix Almendra-Hernández, Miles Bakenhus, Vishesh Karwa +2
A valued stochastic blockmodel (SBM) is a general way to view networked data in which nodes are grouped into blocks and links between them are measured by counts or labels. This fa…
Algebraic statistics, tables, and networks: The Fienberg advantage
Elizabeth Gross, Vishesh Karwa, Sonja Petrović
Stephen Fienberg's affinity for contingency table problems and reinterpreting models with a fresh look gave rise to a new approach for hypothesis testing of network models that are…
A systematic investigation of classical causal inference strategies under mis-specification due to network interference
Vishesh Karwa, Edoardo M. Airoldi
We systematically investigate issues due to mis-specification that arise in estimating causal effects when (treatment) interference is informed by a network available pre-intervent…
Monte Carlo goodness-of-fit tests for degree corrected and related stochastic blockmodels
Vishesh Karwa, Debdeep Pati, Sonja Petrović +6
We construct Bayesian and frequentist finite-sample goodness-of-fit tests for three different variants of the stochastic blockmodel for network data. Since all of the stochastic bl…
DERGMs: Degeneracy-restricted exponential random graph models
Vishesh Karwa, Sonja Petrović, Denis Bajić
Exponential random graph models, or ERGMs, are a flexible and general class of models for modeling dependent data. While the early literature has shown them to be powerful in captu…
Inference using noisy degrees: Differentially private -model and synthetic graphs
Vishesh Karwa, Aleksandra Slavković
The -model of random graphs is an exponential family model with the degree sequence as a sufficient statistic. In this paper, we contribute three key results. First, we characte…