7 citations · 7 across the 1 of their papers we have counts for
3 papers
cs.LG2020
Learning Latent Causal Structures with a Redundant Input Neural Network
Jonathan D. Young, Bryan Andrews, Gregory F. Cooper +1
Most causal discovery algorithms find causal structure among a set of observed variables. Learning the causal structure among latent variables remains an important open problem, pa…
q-bio.MN2018
FASK with Interventional Knowledge Recovers Edges from the Sachs Model
Joseph Ramsey, Bryan Andrews
We report a procedure that, in one step from continuous data with minimal preparation, recovers the graph found by Sachs et al. \cite{sachs2005causal}, with only a few edges differ…
cs.AI2017★ 7 cited
A Comparison of Public Causal Search Packages on Linear, Gaussian Data with No Latent Variables
Joseph D. Ramsey, Bryan Andrews
We compare Tetrad (Java) algorithms to the other public software packages BNT (Bayes Net Toolbox, Matlab), pcalg (R), bnlearn (R) on the \vanilla" task of recovering DAG structure…