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Papers
Causality with Gates
AISTATS 2012
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs
JMLR 2012
Controlling Selection Bias in Causal Inference
AISTATS 2012
Facilitating Score and Causal Inference Trees for Large Observational Studies
JMLR 2012
Statistical test for consistent estimation of causal effects in linear non-Gaussian models
AISTATS 2012
Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies
JMLR 2012
A rational model of causal inference with continuous causes
NeurIPS 2011
Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables
AISTATS 2011
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
NeurIPS 2010
Causal discovery in multiple models from different experiments
NeurIPS 2010
Combining Experiments to Discover Linear Cyclic Models with Latent Variables
AISTATS 2010
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
JMLR 2010
Identifying Cause and Effect on Discrete Data using Additive Noise Models
AISTATS 2010
Introduction to Causal Inference
JMLR 2010
Probabilistic latent variable models for distinguishing between cause and effect
NeurIPS 2010
Sparse Instrumental Variables (SPIV) for Genome-Wide Studies
NeurIPS 2010
Sufficient covariates and linear propensity analysis
AISTATS 2010
Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs
AISTATS 2010
Nonlinear directed acyclic structure learning with weakly additive noise models
NeurIPS 2009
Properties of Monotonic Effects on Directed Acyclic Graphs
JMLR 2009
Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning
JMLR 2009
Subgroup Analysis via Recursive Partitioning
JMLR 2009
Time-Varying Dynamic Bayesian Networks
NeurIPS 2009
Toward Provably Correct Feature Selection in Arbitrary Domains
NeurIPS 2009
Complete Identification Methods for the Causal Hierarchy
JMLR 2008