4 papers
Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows
Sourabh Balgi, Jose M. Peña, Adel Daoud
This work demonstrates the application of a particular branch of causal inference and deep learning models: \emph{causal-Graphical Normalizing Flows (c-GNFs)}. In a recent contribu…
Personalized Public Policy Analysis in Social Sciences using Causal-Graphical Normalizing Flows
Sourabh Balgi, Jose M. Pena, Adel Daoud
Structural Equation/Causal Models (SEMs/SCMs) are widely used in epidemiology and social sciences to identify and analyze the average causal effect (ACE) and conditional ACE (CACE)…
Contradistinguisher: A Vapnik's Imperative to Unsupervised Domain Adaptation
Sourabh Balgi, Ambedkar Dukkipati
A complex combination of simultaneous supervised-unsupervised learning is believed to be the key to humans performing tasks seamlessly across multiple domains or tasks. This phenom…
CUDA: Contradistinguisher for Unsupervised Domain Adaptation
Sourabh Balgi, Ambedkar Dukkipati
In this paper, we propose a simple model referred as Contradistinguisher (CTDR) for unsupervised domain adaptation whose objective is to jointly learn to contradistinguish on unlab…