Eric V. Strobl

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 27

Top Topics

Probabilistic Model

Conditional Dependence

Top Venues

Int. J. Data Sci. Anal.

Publications

Eric V. Strobl, Thomas A. Lasko, Eric R. Gamazon
Mitigating pathogenesis for target discovery and disease subtyping. Comput. Biol. Medicine 171 (2024)
Eric V. Strobl
Counterfactual formulation of patient-specific root causes of disease. J. Biomed. Informatics 150 (2024)
Thomas A. Lasko, John M. Still, Thomas Z. Li, Marco Barbero Mota, William W. Stead, Eric V. Strobl, Bennett A. Landman, Fabien Maldonado
Unsupervised Discovery of Clinical Disease Signatures Using Probabilistic Independence. CoRR (2024)
Thomas A. Lasko, Eric V. Strobl, William W. Stead
Why do probabilistic clinical models fail to transport between sites. npj Digit. Medicine 7 (1) (2024)
Eric V. Strobl
Counterfactual Formulation of Patient-Specific Root Causes of Disease. CoRR (2023)
Eric V. Strobl
Causal discovery with a mixture of DAGs. Mach. Learn. 112 (11) (2023)
Eric V. Strobl
Root Causal Inference from Single Cell RNA Sequencing with the Negative Binomial. BCB (2023)
Eric V. Strobl, Thomas A. Lasko
Identifying patient-specific root causes with the heteroscedastic noise model. J. Comput. Sci. 72 (2023)
Thomas A. Lasko, Eric V. Strobl, William W. Stead
Why Do Clinical Probabilistic Models Fail To Transport Between Sites? CoRR (2023)
Eric V. Strobl, Thomas A. Lasko
Sample-Specific Root Causal Inference with Latent Variables. CLeaR (2023)
Eric V. Strobl, Thomas A. Lasko
Identifying patient-specific root causes of disease. BCB (2022)
Eric V. Strobl, Thomas A. Lasko
Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model. CoRR (2022)
Eric V. Strobl, Thomas A. Lasko
Identifying Patient-Specific Root Causes of Disease. CoRR (2022)
Eric V. Strobl, Thomas A. Lasko
Sample-Specific Root Causal Inference with Latent Variables. CoRR (2022)
Eric V. Strobl, Thomas A. Lasko
Synthesized Difference in Differences. CoRR (2021)
Eric V. Strobl
Automated hyperparameter selection for the PC algorithm. Pattern Recognit. Lett. 151 (2021)
Eric V. Strobl, Shyam Visweswaran
Dirac Delta Regression: Conditional Density Estimation with Clinical Trials. CD@KDD (2021)
Eric V. Strobl, Thomas A. Lasko
Generalizing Clinical Trials with Convex Hulls. CoRR (2021)
Eric V. Strobl, Thomas A. Lasko
Synthesized difference in differences. BCB (2021)
Eric V. Strobl
Automated Hyperparameter Selection for the PC Algorithm. CoRR (2020)
Eric V. Strobl
Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs. CoRR (2019)
Eric V. Strobl, Shyam Visweswaran
Dirac Delta Regression: Conditional Density Estimation with Clinical Trials. CoRR (2019)
Eric V. Strobl
Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs. CD@KDD (2019)
Eric V. Strobl
A constraint-based algorithm for causal discovery with cycles, latent variables and selection bias. Int. J. Data Sci. Anal. 8 (1) (2019)
Eric V. Strobl, Peter L. Spirtes, Shyam Visweswaran
Estimating and Controlling the False Discovery Rate of the PC Algorithm Using Edge-specific P-Values. ACM Trans. Intell. Syst. Technol. 10 (5) (2019)
Eric V. Strobl, Shyam Visweswaran, Peter L. Spirtes
Fast causal inference with non-random missingness by test-wise deletion. Int. J. Data Sci. Anal. 6 (1) (2018)
Eric V. Strobl
A Constraint-Based Algorithm For Causal Discovery with Cycles, Latent Variables and Selection Bias. CoRR (2018)
Eric V. Strobl, Shyam Visweswaran
Dependence versus Conditional Dependence in Local Causal Discovery from Gene Expression Data. CoRR (2014)
Eric V. Strobl, Shyam Visweswaran
Markov Blanket Ranking using Kernel-based Conditional Dependence Measures. CoRR (2014)
Eric V. Strobl, Shyam Visweswaran
Deep Multiple Kernel Learning. ICMLA (1) (2013)
Eric V. Strobl, Shyam Visweswaran
Deep Multiple Kernel Learning. CoRR (2013)