62 citations · 104 across the 14 of their papers we have counts for
4 papers · 1 filter
Model-oriented Graph Distances via Partially Ordered Sets
Armeen Taeb, F. Richard Guo, Leonard Henckel
A well-defined distance on the parameter space is key to evaluating estimators, ensuring consistency, and building confidence sets. While there are typically standard distances to…
Embracing Discrete Search: A Reasonable Approach to Causal Structure Learning
Marcel Wienöbst, Leonard Henckel, Sebastian Weichwald
We present FLOP (Fast Learning of Order and Parents), a score-based causal discovery algorithm for linear models. It pairs fast parent selection with iterative Cholesky-based score…
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference
Marcel Wienöbst, Sebastian Weichwald, Leonard Henckel
We introduce CIfly, a framework for efficient algorithmic primitives in graphical causal inference that isolates reachability as a reusable core operation. It builds on the insight…
Causal inference amid missingness-specific independencies and mechanism shifts
Johan de Aguas, Leonard Henckel, Johan Pensar +1
The recovery of causal effects in structural models with missing data often relies on -graphs, which assume that missingness mechanisms do not directly influence substantive var…