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Thijs van Ommen
Thijs van Ommen
Assistant Professor at Utrecht University
Verified email at uu.nl
Title
Cited by
Cited by
Year
Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it
P Grünwald, T van Ommen
Bayesian Analysis 12 (4), 1069-1103, 2017
2782017
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
S Magliacane, T van Ommen, T Claassen, S Bongers, P Versteeg, ...
Advances in Neural Information Processing Systems, 10869-10879, 2018
2282018
Algebraic Equivalence of Linear Structural Equation Models
T van Ommen, JM Mooij
Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence …, 2017
132017
Robust probability updating
T van Ommen, WM Koolen, TE Feenstra, PD Grünwald
International Journal of Approximate Reasoning 74, 30-57, 2016
62016
Better predictions when models are wrong or underspecified
M Ommen
Faculty of Science, Leiden University, 2015
62015
Robust Causal Domain Adaptation in a Simple Diagnostic Setting
T van Ommen
International Symposium on Imprecise Probabilities: Theories and …, 2019
22019
Computing Minimax Decisions with Incomplete Observations
T van Ommen
Proceedings of the Tenth International Symposium on Imprecise Probability …, 2017
22017
Causal Entropy and Information Gain for Measuring Causal Control
FNFQ Simoes, M Dastani, T van Ommen
European Conference on Artificial Intelligence, 216-231, 2023
12023
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models
T van Ommen, M Drton
International Conference on Probabilistic Graphical Models, 409-420, 2022
12022
Learning Bayesian Networks by Branching on Constraints
T van Ommen
International Conference on Probabilistic Graphical Models, 511-522, 2018
12018
Causal blind spots when using prediction models for treatment decisions
N van Geloven, RH Keogh, W van Amsterdam, G Cinà, JH Krijthe, N Peek, ...
arXiv preprint arXiv:2402.17366, 2024
2024
Fundamental Properties of Causal Entropy and Information Gain
FNFQ Simoes, M Dastani, T van Ommen
arXiv preprint arXiv:2402.01341, 2024
2024
Risk-based decision making: estimands for sequential prediction under interventions
K Luijken, P Morzywołek, W van Amsterdam, G Cinà, J Hoogland, ...
arXiv preprint arXiv:2311.17547, 2023
2023
Causal Entropy and Information Gain for Measuring Causal Control
F Nunes Ferreira Quialheiro Simoes, M Dastani, T van Ommen
arXiv e-prints, arXiv: 2309.07703, 2023
2023
Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness
T van Ommen, WM Koolen, PD Grünwald
Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 15th …, 2019
2019
Combining predictions from linear models when training and test inputs differ
T van Ommen
Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence …, 2014
2014
AIC for Conditional Model Selection
T van Ommen
BENELEARN 2013, 2013
2013
ADAPTING AIC TO CONDITIONAL MODEL SELECTION
T van Ommen
FIFTH WORKSHOP ON INFORMATION THEORETIC METHODS IN SCIENCE AND ENGINEERING, 4, 2012
2012
The Assignment Problem on Sets of Strings
T van Ommen
LIACS, Universiteit Leiden, 2012
2012
A Statistical Method for the Evaluation of Compiler Switches
T van Ommen
2005
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