Thijs van Ommen

23 papers A* 1A 4C 1Journal 11Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	The Causal Information Bottleneck and Optimal Causal Variable Abstractions. UAI Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2025	J	`jnl`	The Minimal Search Space for Conditional Causal Bandits. CoRR Francisco Nunes Ferreira Quialheiro Simoes, Itai Feigenbaum, Mehdi Dastani, Thijs van Ommen
2024	A	`conf`	Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path Diagrams. UAI Thijs van Ommen
2024	J	`jnl`	Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path Diagrams. CoRR Thijs van Ommen
2024	—	`conf`	Fundamental Properties of Causal Entropy and Information Gain. CLeaR Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2024	J	`jnl`	Fundamental Properties of Causal Entropy and Information Gain. CoRR Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2024	J	`jnl`	Optimal Causal Representations and the Causal Information Bottleneck. CoRR Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2023	—	`conf`	Causal Entropy and Information Gain for Measuring Causal Control. ECAI Workshops (1) Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2023	J	`jnl`	Causal Entropy and Information Gain for Measuring Causal Control. CoRR Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen
2022	—	`conf`	Graphical Representations for Algebraic Constraints of Linear Structural Equations Models. PGM Thijs van Ommen, Mathias Drton
2022	J	`jnl`	Graphical Representations for Algebraic Constraints of Linear Structural Equations Models. CoRR Thijs van Ommen, Mathias Drton
2019	C	`conf`	Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness. ECSQARU Thijs van Ommen, Wouter M. Koolen, Peter D. Grünwald
2019	—	`conf`	Robust Causal Domain Adaptation in a Simple Diagnostic Setting. ISIPTA Thijs van Ommen
2018	J	`jnl`	Algebraic Equivalence of Linear Structural Equation Models. CoRR Thijs van Ommen, Joris M. Mooij
2018	A*	`conf`	Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions. NeurIPS Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij
2018	—	`conf`	Learning Bayesian Networks by Branching on Constraints. PGM Thijs van Ommen
2017	A	`conf`	Algebraic Equivalence Class Selection for Linear Structural Equation Models. UAI Thijs van Ommen, Joris M. Mooij
2017	J	`jnl`	Causal Transfer Learning. CoRR Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij
2017	—	`conf`	Computing Minimax Decisions with Incomplete Observations. ISIPTA Thijs van Ommen
2016	J	`jnl`	Robust probability updating. Int. J. Approx. Reason. Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald
2015	J	`jnl`	Worst-case Optimal Probability Updating. CoRR Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald
2014	A	`conf`	Combining predictions from linear models when training and test inputs differ. UAI Thijs van Ommen
2014	J	`jnl`	Combining predictions from linear models when training and test inputs differ. CoRR Thijs van Ommen