Eric V. Strobl | DeepAI

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Kun Zhang
106 publications
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12 publications
Peter L. Spirtes
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∙ 05/27/2023

Counterfactual Formulation of Patient-Specific Root Causes of Disease

Root causes of disease intuitively correspond to root vertices that incr...

0 Eric V. Strobl, et al. ∙

∙ 10/27/2022

Sample-Specific Root Causal Inference with Latent Variables

Root causal analysis seeks to identify the set of initial perturbations ...

0 Eric V. Strobl, et al. ∙

∙ 05/25/2022

Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model

Complex diseases are caused by a multitude of factors that may differ be...

0 Eric V. Strobl, et al. ∙

∙ 05/23/2022

Identifying Patient-Specific Root Causes of Disease

Complex diseases are caused by a multitude of factors that may differ be...

0 Eric V. Strobl, et al. ∙

∙ 11/25/2021

Generalizing Clinical Trials with Convex Hulls

Randomized clinical trials eliminate confounding but impose strict exclu...

0 Eric V. Strobl, et al. ∙

∙ 05/02/2021

Synthesized Difference in Differences

Randomized clinical trials (RCTs) eliminate confounding but impose stric...

0 Eric V. Strobl, et al. ∙

∙ 11/03/2020

Automated Hyperparameter Selection for the PC Algorithm

The PC algorithm infers causal relations using conditional independence ...

0 Eric V. Strobl, et al. ∙

∙ 09/12/2019

The Global Markov Property for a Mixture of DAGs

Real causal processes may contain feedback loops and change over time. I...

0 Eric V. Strobl, et al. ∙

∙ 05/24/2019

Dirac Delta Regression: Conditional Density Estimation with Clinical Trials

Personalized medicine seeks to identify the causal effect of treatment f...

0 Eric V. Strobl, et al. ∙

∙ 01/28/2019

Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs

Many causal processes in biomedicine contain cycles and evolve. However,...

0 Eric V. Strobl, et al. ∙

∙ 05/05/2018

A Constraint-Based Algorithm For Causal Discovery with Cycles, Latent Variables and Selection Bias

Causal processes in nature may contain cycles, and real datasets may vio...

0 Eric V. Strobl, et al. ∙

∙ 05/25/2017

Fast Causal Inference with Non-Random Missingness by Test-Wise Deletion

Many real datasets contain values missing not at random (MNAR). In this ...

0 Eric V. Strobl, et al. ∙

∙ 02/13/2017

Approximate Kernel-based Conditional Independence Tests for Fast Non-Parametric Causal Discovery

Constraint-based causal discovery (CCD) algorithms require fast and accu...

0 Eric V. Strobl, et al. ∙

∙ 07/14/2016

Estimating and Controlling the False Discovery Rate for the PC Algorithm Using Edge-Specific P-Values

The PC algorithm allows investigators to estimate a complete partially d...

0 Eric V. Strobl, et al. ∙

∙ 09/14/2015

Markov Boundary Discovery with Ridge Regularized Linear Models

Ridge regularized linear models (RRLMs), such as ridge regression and th...

0 Eric V. Strobl, et al. ∙

∙ 07/28/2014

Dependence versus Conditional Dependence in Local Causal Discovery from Gene Expression Data

Motivation: Algorithms that discover variables which are causally relate...

0 Eric V. Strobl, et al. ∙

∙ 02/01/2014

Markov Blanket Ranking using Kernel-based Conditional Dependence Measures

Developing feature selection algorithms that move beyond a pure correlat...

0 Eric V. Strobl, et al. ∙

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