3 citations · 4 across the 11 of their papers we have counts for
11 papers
Causal Inference with Unobserved Confounding: A Mixture Learning Perspective
Mansi Sood, Devavrat Shah
Unobserved confounding is a fundamental challenge in causal inference from observational data. This article develops a mixture-learning perspective, viewing latent confounders as s…
On Balancing Sparsity with Reliable Connectivity in Distributed Network Design with Random K-out Graphs
Mansi Sood, Eray Can Elumar, Osman Yagan
In several applications in distributed systems, an important design criterion is ensuring that the network is sparse, i.e., does not contain too many edges, while achieving reliabl…
On the Interplay of Clustering and Evolution in the Emergence of Epidemic Outbreaks
Mansi Sood, Hejin Gu, Rashad Eletreby +3
In an increasingly interconnected world, a key scientific challenge is to examine mechanisms that lead to the widespread propagation of contagions, such as misinformation and patho…
On the Robustness, Connectivity and Giant Component Size of Random K-out Graphs
Eray Can Elumar, Mansi Sood, Osman Yağan
Random K-out graphs are garnering interest in designing distributed systems including secure sensor networks, anonymous crypto-currency networks, and differentially-private decentr…
Spreading Processes with Mutations over Multi-layer Networks
Mansi Sood, Anirudh Sridhar, Rashad Eletreby +4
A key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under different countermeasures that limit interact…
On the Connectivity and Giant Component Size of Random K-out Graphs Under Randomly Deleted Nodes
Eray Can Elumar, Mansi Sood, Osman Yagan
Random K-out graphs, denoted , are generated by each of the nodes drawing out-edges towards distinct nodes selected uniformly at random, and then ignor…