4 papers
Coarsening Causal DAG Models
Francisco Madaleno, Pratik Misra, Alex Markham
Directed acyclic graphical (DAG) models are a powerful tool for representing causal relationships among jointly distributed random variables, especially concerning data from across…
Linear relations of colored Gaussian cycles
Hannah Göbel, Pratik Misra
A colored Gaussian graphical model is a linear concentration model in which equalities among the concentrations are specified by a coloring of an underlying graph. Marigliano and D…
Addressing pitfalls in implicit unobserved confounding synthesis using explicit block hierarchical ancestral sampling
Xudong Sun, Alex Markham, Pratik Misra +1
Unbiased data synthesis is crucial for evaluating causal discovery algorithms in the presence of unobserved confounding, given the scarcity of real-world datasets. A common approac…
Homaloidal Polynomials and Gaussian Models of Maximum Likelihood Degree One
Shelby Cox, Pratik Misra, Pardis Semnani
We study the Gaussian statistical models whose log-likelihood function has a unique complex critical point, i.e., has maximum likelihood degree one. We exploit the connection devel…