Eric V. Strobl

41 papers Journal 31Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Extracting Root-Causal Brain Activity Driving Psychopathology from Resting State fMRI. CoRR Eric V. Strobl
2026	J	`jnl`	Global Interpretability via Automated Preprocessing: A Framework Inspired by Psychiatric Questionnaires. CoRR Eric V. Strobl
2025	J	`jnl`	A data-driven approach to discover and quantify systemic lupus erythematosus etiological heterogeneity from electronic health records. CoRR Marco Barbero Mota, John M. Still, Jorge L. Gamboa, Eric V. Strobl, Charles M. Stein, Vivian K. Kawai, Thomas A. Lasko
2025	J	`jnl`	A tutorial on discovering and quantifying the effect of latent causal sources of multimodal EHR data. CoRR Marco Barbero Mota, Eric V. Strobl, John M. Still, William W. Stead, Thomas A. Lasko
2025	J	`jnl`	Learning Causally Predictable Outcomes from Psychiatric Longitudinal Data. CoRR Eric V. Strobl
2025	—	`conf`	Predicting the Predictable in the Psychiatric High Risk. MLHC Eric V. Strobl
2025	J	`jnl`	Transcriptome-wide root causal inference. PLoS Comput. Biol. Eric V. Strobl, Eric R. Gamazon
2025	J	`jnl`	Unsupervised discovery of clinical disease signatures using probabilistic independence. J. Biomed. Informatics Thomas A. Lasko, William W. Stead, John M. Still, Thomas Z. Li, Michael N. Kammer, Marco Barbero Mota, Eric V. Strobl, Bennett A. Landman, Fabien Maldonado
2024	J	`jnl`	Counterfactual formulation of patient-specific root causes of disease. J. Biomed. Informatics Eric V. Strobl
2024	J	`jnl`	Mitigating pathogenesis for target discovery and disease subtyping. Comput. Biol. Medicine Eric V. Strobl, Thomas A. Lasko, Eric R. Gamazon
2024	J	`jnl`	Unsupervised Discovery of Clinical Disease Signatures Using Probabilistic Independence. CoRR Thomas A. Lasko, John M. Still, Thomas Z. Li, Marco Barbero Mota, William W. Stead, Eric V. Strobl, Bennett A. Landman, Fabien Maldonado
2024	J	`jnl`	Why do probabilistic clinical models fail to transport between sites. npj Digit. Medicine Thomas A. Lasko, Eric V. Strobl, William W. Stead
2023	J	`jnl`	Causal discovery with a mixture of DAGs. Mach. Learn. Eric V. Strobl
2023	J	`jnl`	Counterfactual Formulation of Patient-Specific Root Causes of Disease. CoRR Eric V. Strobl
2023	—	`conf`	Generalizing Clinical Trials with Convex Hulls. CLeaR Eric V. Strobl, Thomas A. Lasko
2023	J	`jnl`	Identifying patient-specific root causes with the heteroscedastic noise model. J. Comput. Sci. Eric V. Strobl, Thomas A. Lasko
2023	—	`conf`	Root Causal Inference from Single Cell RNA Sequencing with the Negative Binomial. BCB Eric V. Strobl
2023	—	`conf`	Sample-Specific Root Causal Inference with Latent Variables. CLeaR Eric V. Strobl, Thomas A. Lasko
2023	J	`jnl`	Why Do Clinical Probabilistic Models Fail To Transport Between Sites? CoRR Thomas A. Lasko, Eric V. Strobl, William W. Stead
2022	J	`jnl`	Identifying Patient-Specific Root Causes of Disease. CoRR Eric V. Strobl, Thomas A. Lasko
2022	J	`jnl`	Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model. CoRR Eric V. Strobl, Thomas A. Lasko
2022	—	`conf`	Identifying patient-specific root causes of disease. BCB Eric V. Strobl, Thomas A. Lasko
2022	J	`jnl`	Sample-Specific Root Causal Inference with Latent Variables. CoRR Eric V. Strobl, Thomas A. Lasko
2021	J	`jnl`	Automated hyperparameter selection for the PC algorithm. Pattern Recognit. Lett. Eric V. Strobl
2021	—	`conf`	Dirac Delta Regression: Conditional Density Estimation with Clinical Trials. CD@KDD Eric V. Strobl, Shyam Visweswaran
2021	J	`jnl`	Generalizing Clinical Trials with Convex Hulls. CoRR Eric V. Strobl, Thomas A. Lasko
2021	J	`jnl`	Synthesized Difference in Differences. CoRR Eric V. Strobl, Thomas A. Lasko
2021	—	`conf`	Synthesized difference in differences. BCB Eric V. Strobl, Thomas A. Lasko
2020	J	`jnl`	Automated Hyperparameter Selection for the PC Algorithm. CoRR Eric V. Strobl
2019	J	`jnl`	A constraint-based algorithm for causal discovery with cycles, latent variables and selection bias. Int. J. Data Sci. Anal. Eric V. Strobl
2019	J	`jnl`	Dirac Delta Regression: Conditional Density Estimation with Clinical Trials. CoRR Eric V. Strobl, Shyam Visweswaran
2019	J	`jnl`	Estimating and Controlling the False Discovery Rate of the PC Algorithm Using Edge-specific P-Values. ACM Trans. Intell. Syst. Technol. Eric V. Strobl, Peter L. Spirtes, Shyam Visweswaran
2019	—	`conf`	Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs. CD@KDD Eric V. Strobl
2019	J	`jnl`	Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs. CoRR Eric V. Strobl
2019	—	`ch.`	Markov Blanket Ranking Using Kernel-Based Conditional Dependence Measures. Cause Effect Pairs in Machine Learning Eric V. Strobl, Shyam Visweswaran
2018	J	`jnl`	A Constraint-Based Algorithm For Causal Discovery with Cycles, Latent Variables and Selection Bias. CoRR Eric V. Strobl
2018	J	`jnl`	Fast causal inference with non-random missingness by test-wise deletion. Int. J. Data Sci. Anal. Eric V. Strobl, Shyam Visweswaran, Peter L. Spirtes
2014	J	`jnl`	Dependence versus Conditional Dependence in Local Causal Discovery from Gene Expression Data. CoRR Eric V. Strobl, Shyam Visweswaran
2014	J	`jnl`	Markov Blanket Ranking using Kernel-based Conditional Dependence Measures. CoRR Eric V. Strobl, Shyam Visweswaran
2013	—	`conf`	Deep Multiple Kernel Learning. ICMLA (1) Eric V. Strobl, Shyam Visweswaran
2013	J	`jnl`	Deep Multiple Kernel Learning. CoRR Eric V. Strobl, Shyam Visweswaran