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ORCIDThijs van Ommen
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2020 – today
- 2024
[c10]Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen:
Fundamental Properties of Causal Entropy and Information Gain. CLeaR 2024: 188-208- [i9]Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen:
Fundamental Properties of Causal Entropy and Information Gain. CoRR abs/2402.01341 (2024) - [i8]Thijs van Ommen:
Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path Diagrams. CoRR abs/2406.09049 (2024) - [i7]Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen:
Optimal Causal Representations and the Causal Information Bottleneck. CoRR abs/2410.00535 (2024) - 2023
- [c9]Francisco Nunes Ferreira Quialheiro Simoes
, Mehdi Dastani, Thijs van Ommen:
Causal Entropy and Information Gain for Measuring Causal Control. ECAI Workshops (1) 2023: 216-231 - [i6]Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen:
Causal Entropy and Information Gain for Measuring Causal Control. CoRR abs/2309.07703 (2023) - 2022
- [c8]Thijs van Ommen, Mathias Drton:
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models. PGM 2022: 409-420 - [i5]Thijs van Ommen, Mathias Drton:
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models. CoRR abs/2208.00926 (2022)
2010 – 2019
- 2019
- [c7]Thijs van Ommen, Wouter M. Koolen, Peter D. Grünwald:
Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness. ECSQARU 2019: 336-347 - [c6]Thijs van Ommen:
Robust Causal Domain Adaptation in a Simple Diagnostic Setting. ISIPTA 2019: 424-429 - 2018
- [c5]Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij:
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions. NeurIPS 2018: 10869-10879 - [c4]Thijs van Ommen:
Learning Bayesian Networks by Branching on Constraints. PGM 2018: 511-522 - [i4]Thijs van Ommen, Joris M. Mooij:
Algebraic Equivalence of Linear Structural Equation Models. CoRR abs/1807.03527 (2018) - 2017
- [c3]Thijs van Ommen:
Computing Minimax Decisions with Incomplete Observations. ISIPTA 2017: 358-369 - [c2]Thijs van Ommen, Joris M. Mooij:
Algebraic Equivalence Class Selection for Linear Structural Equation Models. UAI 2017 - [i3]Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij:
Causal Transfer Learning. CoRR abs/1707.06422 (2017) - 2016
- [j1]Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald:
Robust probability updating. Int. J. Approx. Reason. 74: 30-57 (2016) - 2015
- [i2]Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald:
Worst-case Optimal Probability Updating. CoRR abs/1512.03223 (2015) - 2014
- [c1]Thijs van Ommen:
Combining predictions from linear models when training and test inputs differ. UAI 2014: 653-662 - [i1]Thijs van Ommen:
Combining predictions from linear models when training and test inputs differ. CoRR abs/1406.6200 (2014)
Coauthor Index
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last updated on 2024-11-06 21:33 CET by the dblp team
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