Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness. - Ioan Gabriel Bucur; Tom Claassen; Tom Heskes (AISTATS, 2017)

A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks. - Ioan Gabriel Bucur; Tom van Bussel; Tom Claassen; Tom Heskes (PGM, 2018)

Large-scale local causal inference of gene regulatory relationships. - Ioan Gabriel Bucur; Tom Claassen; Tom Heskes (Int. J. Approx. Reason., 2019)

A novel Bayesian approach for latent variable modeling from mixed data with missing values. - Ruifei Cui; Ioan Gabriel Bucur; Perry Groot; Tom Heskes (Stat. Comput., 2019)

Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models. - Tom Heskes; Evi Sijben; Ioan Gabriel Bucur; Tom Claassen (NeurIPS, 2020)

MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models. - Ioan Gabriel Bucur; Tom Claassen; Tom Heskes (UAI, 2020)

Greedy equivalence search in the presence of latent confounders. - Tom Claassen; Ioan Gabriel Bucur (UAI, 2022)

Beyond the Markov Equivalence Class: Extending Causal Discovery under Latent Confounding. - Mirthe Maria Van Diepen; Ioan Gabriel Bucur; Tom Heskes; Tom Claassen (CLeaR, 2023)

A Tale of Snakes and Horses: Amplifying Correlation Power Analysis on Quadratic Maps. - Anna Guinet; Georg Land; Ioan Gabriel Bucur; Tim Güneysu (IACR Trans. Cryptogr. Hardw. Embed. Syst., 2024)