Bounding Causal Effects with Leaky Instruments

1 code implementation • 5 Apr 2024 • David S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo-Hermsdorff, Afsaneh Mastouri, Ricardo Silva

Instrumental variables (IVs) are a popular and powerful tool for estimating causal effects in the presence of unobserved confounding.

Quantifying Human Priors over Social and Navigation Networks

no code implementations • 28 Feb 2024 • Gecia Bravo-Hermsdorff

In this work, we leverage the combinatorial structure of graphs to quantify human priors over such relational data.

Private and Communication-Efficient Algorithms for Entropy Estimation

no code implementations • 12 May 2023 • Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Muñoz Medina, Umar Syed

For a joint distribution over many variables whose conditional independence is given by a tree, we describe algorithms for estimating Shannon entropy that require a number of samples that is linear in the number of variables, compared to the quadratic sample complexity of prior work.

Introducing Graph Cumulants: What is the Variance of Your Social Network?

1 code implementation • 10 Feb 2020 • Lee M. Gunderson, Gecia Bravo-Hermsdorff

In an increasingly interconnected world, understanding and summarizing the structure of these networks becomes increasingly relevant.

Statistics Theory Discrete Mathematics Social and Information Networks Physics and Society Statistics Theory