conftrace_

structural equation model

77 papers

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Also known as

SEM

Co-occurring keywords

causal discovery (460) causal inference (1630) graphical model (864) directed acyclic graph (245) latent variable (541) causal graph (140) causal model (57) additive noise model (26) linear structural equation model (13) bayesian network (378)

Papers

Triad Constraints for Learning Causal Structure of Latent Variables NIPS 2019
On Open-Universe Causal Reasoning UAI 2019
Stability of Linear Structural Equation Models of Causal Inference UAI 2019
High-Dimensional Poisson Structural Equation Model Learning via $\ell_1$-Regularized Regression JMLR 2019
Learning linear structural equation models in polynomial time and sample complexity AISTATS 2018
On the Conditional Logic of Simulation Models IJCAI 2018
Actual Causality in a Logical Setting IJCAI 2018
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables ICML 2017
Identification and Overidentification of Linear Structural Equation Models NIPS 2016
Learning Acyclic Directed Mixed Graphs from Observations and Interventions PGM 2016
Estimating Causal Effects with Ancestral Graph Markov Models PGM 2016
Learning Causal Graphs with Small Interventions NIPS 2015
Bayesian Estimation of Causal Direction in Acyclic Structural Equation Models with Individual-specific Confounder Variables and Non-Gaussian Distributions JMLR 2014
Causal Discovery with Continuous Additive Noise Models JMLR 2014
Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models JMLR 2013
Causal Inference on Time Series using Restricted Structural Equation Models NIPS 2013
SADA: A General Framework to Support Robust Causation Discovery ICML 2013
Causal discovery with scale-mixture model for spatiotemporal variance dependencies NIPS 2012
DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model JMLR 2011
Structural equations and divisive normalization for energy-dependent component analysis NIPS 2011
Combining Experiments to Discover Linear Cyclic Models with Latent Variables AISTATS 2010
Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs AISTATS 2010
Markov Properties for Linear Causal Models with Correlated Errors JMLR 2009
Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors JMLR 2009
Nonlinear causal discovery with additive noise models NIPS 2008