| 2025 | AISTATS | SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph. | Mtys Schubert, Tom Claassen, Sara Magliacane |
| 2023 | UAI | Establishing Markov equivalence in cyclic directed graphs. | Tom Claassen, Joris M. Mooij |
| 2022 | UAI | Greedy equivalence search in the presence of latent confounders. | Tom Claassen, Ioan Gabriel Bucur |
| 2020 | UAI | MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models. | Ioan Gabriel Bucur, Tom Claassen, Tom Heskes |
| 2020 | UAI | Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles. | Joris M. Mooij, Tom Claassen |
| 2017 | AISTATS | Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness. | Ioan Gabriel Bucur, Tom Claassen, Tom Heskes |
| 2015 | AIME | Causal Discovery from Medical Data: Dealing with Missing Values and a Mixture of Discrete and Continuous Data. | Elena Sokolova, Perry Groot, Tom Claassen, Daniel von Rhein, Jan K. Buitelaar, Tom Heskes |
| 2013 | IJCAI | Bayesian Probabilities for Constraint-Based Causal Discovery. | Tom Claassen, Tom Heskes |
| 2013 | UAI | Learning Sparse Causal Models is not NP-hard. | Tom Claassen, Joris M. Mooij, Tom Heskes |
| 2012 | UAI | A Bayesian Approach to Constraint Based Causal Inference. | Tom Claassen, Tom Heskes |
| 2011 | ESANN | A structure independent algorithm for causal discovery. | Tom Claassen, Tom Heskes |
| 2011 | UAI | A Logical Characterization of Constraint-Based Causal Discovery. | Tom Claassen, Tom Heskes |