3 papers
stat.ML2026
Falsifying Causal Graphs With Outlier Events
William Roy Orchard, Philipp M. Faller, Dominik Janzing
True causal relationships are rarely known, and inferring causal graphs from data is hard. A fundamental challenge is how to assess whether a given causal graph is good in the abse…
cs.LG2025
From Guess2Graph: When and How Can Unreliable Experts Safely Boost Causal Discovery in Finite Samples?
Sujai Hiremath, Dominik Janzing, Philipp Faller +4
Causal discovery algorithms often perform poorly with limited samples. While integrating expert knowledge (including from LLMs) as constraints promises to improve performance, guar…
cs.LG2025
On Different Notions of Redundancy in Conditional-Independence-Based Discovery of Graphical Models
Philipp M. Faller, Dominik Janzing
Conditional-independence-based discovery uses statistical tests to identify a graphical model that represents the independence structure of variables in a dataset. These tests, how…