351 citations · 1.2k across the 48 of their papers we have counts for
4 papers · 1 filter
Causal Discovery in the Presence of Measurement Error: Identifiability Conditions
Kun Zhang, Mingming Gong, Joseph Ramsey +3
Measurement error in the observed values of the variables can greatly change the output of various causal discovery methods. This problem has received much attention in multiple fi…
A New Measure of Conditional Dependence
Jalal Etesami, Kun Zhang, Negar Kiyavash
Measuring conditional dependencies among the variables of a network is of great interest to many disciplines. This paper studies some shortcomings of the existing dependency measur…
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash +1
We study causal inference in a multi-environment setting, in which the functional relations for producing the variables from their direct causes remain the same across environments…
Approximate Kernel-based Conditional Independence Tests for Fast Non-Parametric Causal Discovery
Eric V. Strobl, Kun Zhang, Shyam Visweswaran
Constraint-based causal discovery (CCD) algorithms require fast and accurate conditional independence (CI) testing. The Kernel Conditional Independence Test (KCIT) is currently one…