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Maximum Likelihood Estimation for Brownian Motion Tree Models Based on One Sample

Nov 1, 2026
The DeCAMFounder: Non-Linear Causal Discovery in the Presence of Hidden Variables

Jul 13, 2023
Causal Structure Learning: a Combinatorial Perspective

Aug 1, 2022
DCI: Learning Causal Differences between Gene Regulatory Networks

Difference causal inference (DCI) identifies changes in gene regulatory relationships across two conditions directly from their expression data. Rather than reconstructing both complete networks, the algorithm estimates which causal edges appear, disappear, or change strength, reducing sample and computational requirements. A Python implementation includes stability selection across tuning parameters. Applications to single-cell RNA sequencing illustrate network comparison and validation through intervention-effect prediction.

Sep 1, 2021
Causal Network Models of SARS-CoV-2 Expression and Aging to Identify Candidates for Drug Repurposing

Feb 15, 2021