James M. Robins

CoRR, 2024

2022

Causal and counterfactual views of missing data models.

[BibT_eX]

[DOI]

CoRR, 2022

Deep Learning Methods for Proximal Inference via Maximum Moment Restriction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multivariate Counterfactual Systems and Causal Graphical Models.

[BibT_eX]

[DOI]

Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

An Interventionist Approach to Mediation Analysis.

[BibT_eX]

[DOI]

Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021

Adaptive estimation of nonparametric functionals.

[BibT_eX]

[DOI]

Lin Liu

Rajarshi Mukherjee

Eric Tchetgen Tchetgen

J. Mach. Learn. Res., 2021

2019

On assumption-free tests and confidence intervals for causal effects estimated by machine learning.

[BibT_eX]

[DOI]

Lin Liu

Rajarshi Mukherjee

CoRR, 2019

Identification In Missing Data Models Represented By Directed Acyclic Graphs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2015

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations.

[BibT_eX]

[DOI]

Kirthevasan Kandasamy

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations.

[BibT_eX]

[DOI]

Kirthevasan Kandasamy

CoRR, 2014

2013

Sparse Nested Markov models with Log-linear Parameters.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012

Nested Markov Properties for Acyclic Directed Mixed Graphs.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011

Efficient Nonparametric Conformal Prediction Regions

[BibT_eX]

[DOI]

Jing Lei

Larry A. Wasserman

CoRR, 2011

An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models.

[BibT_eX]

[DOI]

Proceedings of the UAI 2011, 2011

2010

On the Validity of Covariate Adjustment for Estimating Causal Effects.

[BibT_eX]

[DOI]

Tyler J. VanderWeele

Proceedings of the UAI 2010, 2010

2009

Properties of Monotonic Effects on Directed Acyclic Graphs.

[BibT_eX]

[DOI]

Tyler J. VanderWeele

J. Mach. Learn. Res., 2009

Testing Edges by Truncations.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2009, 2009

2003

Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures.

[BibT_eX]

[DOI]

Sündüz Keles

Mark J. van der Laan

Proceedings of the Advances in Survival Analysis, 2003

1999

Association, Causation, And Marginal Structural Models.

[BibT_eX]

[DOI]

Synth., 1999

1997

Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs.

[BibT_eX]

[DOI]

Larry A. Wasserman

Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

1995

Probabilistic evaluation of sequential plans from causal models with hidden variables.

[BibT_eX]

[DOI]

Judea Pearl