Claassen, Tom

22 publications

AISTATS 2025 SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation with an Unknown Graph Mátyás Schubert, Tom Claassen, Sara Magliacane

PGM 2024 AutoCD: Automated Machine Learning for Causal Discovery Algorithms Gerlise Chan, Tom Claassen, Holger H. Hoos, Tom Heskes, Mitra Baratchi

CLeaR 2023 Beyond the Markov Equivalence Class: Extending Causal Discovery Under Latent Confounding Mirthe Maria Van Diepen, Ioan Gabriel Bucur, Tom Heskes, Tom Claassen

UAI 2023 Establishing Markov Equivalence in Cyclic Directed Graphs Tom Claassen, Joris M. Mooij

UAI 2022 Greedy Equivalence Search in the Presence of Latent Confounders Tom Claassen, Ioan G. Bucur

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

UAI 2020 Constraint-Based Causal Discovery Using Partial Ancestral Graphs in the Presence of Cycles Joris M. Mooij, Tom Claassen

PGM 2020 Discovering Cause-Effect Relationships in Spatial Systems with a Known Direction Based on Observational Data Konrad P Mielke, Tom Claassen, J Huijbregts, Aafke M Schipper, Tom M Heskes

JMLR 2020 Joint Causal Inference from Multiple Contexts Joris M. Mooij, Sara Magliacane, Tom Claassen

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

PGM 2018 A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks Ioan Gabriel Bucur, Tom Bussel, Tom Claassen, Tom Heskes

NeurIPS 2018 Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij

AISTATS 2017 Robust Causal Estimation in the Large-Sample Limit Without Strict Faithfulness Ioan Gabriel Bucur, Tom Claassen, Tom Heskes

NeurIPS 2016 Ancestral Causal Inference Sara Magliacane, Tom Claassen, Joris M. Mooij

PGM 2016 Computing Lower and Upper Bounds on the Probability of Causal Statements Elena Sokolova, Martine Hoogman, Perry Groot, Tom Claassen, Tom Heskes

UAI 2015 Proceedings of the UAI 2015 Workshop on Advances in Causal Inference Co-Located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, the Netherlands, July 16, 2015 Ricardo Silva, Ilya Shpitser, Robin J. Evans, Jonas Peters, Tom Claassen

UAI 2014 Proceedings of the UAI 2014 Workshop Causal Inference: Learning and Prediction Co-Located with 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), Quebec City, Canada, July 27, 2014 Joris M. Mooij, Dominik Janzing, Jonas Peters, Tom Claassen, Antti Hyttinen

IJCAI 2013 Bayesian Probabilities for Constraint-Based Causal Discovery Tom Claassen, Tom Heskes

UAI 2013 Learning Sparse Causal Models Is Not NP-Hard Tom Claassen, Joris M. Mooij, Tom Heskes

UAI 2012 A Bayesian Approach to Constraint Based Causal Inference Tom Claassen, Tom Heskes

UAI 2011 A Logical Characterization of Constraint-Based Causal Discovery Tom Claassen, Tom Heskes

NeurIPS 2010 Causal Discovery in Multiple Models from Different Experiments Tom Claassen, Tom Heskes