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Antti Hyttinen
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Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming.
A Hyttinen, F Eberhardt, M Järvisalo
UAI, 340-349, 2014
1142014
Learning Linear Cyclic Causal Models with Latent Variables
A Hyttinen, F Eberhardt, PO Hoyer
Journal of Machine Learning Research 13, 3387-3439, 2012
1022012
Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure
A Hyttinen, PO Hoyer, F Eberhardt, M Järvisalo
Uncertainty in Artificial Intelligence, 2013
872013
Experiment selection for causal discovery
A Hyttinen, F Eberhardt, PO Hoyer
Journal of Machine Learning Research 14, 3041-3071, 2013
742013
Do-calculus when the True Graph Is Unknown.
A Hyttinen, F Eberhardt, M Järvisalo
UAI, 395-404, 2015
432015
Causal Discovery from Subsampled Time Series Data by Constraint Optimization
A Hyttinen, S Plis, M Järvisalo, F Eberhardt, D Danks
International Conference on Probabilistic Graphical Models (PGM), 2016
312016
Bayesian discovery of linear acyclic causal models
PO Hoyer, A Hyttinen
Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence …, 2012
292012
A logical approach to context-specific independence
J Corander, A Hyttinen, J Kontinen, J Pensar, J Väänänen
Annals of Pure and Applied Logic 170 (9), 975-992, 2019
232019
Learning Optimal Chain Graphs with Answer Set Programming
D Sonntag, M Järvisalo, JM Pena, A Hyttinen
http://auai.org/uai2015/proceedings/papers/189.pdf, 2015
232015
Reduced cost fixing in MaxSAT
F Bacchus, A Hyttinen, M Järvisalo, P Saikko
International Conference on Principles and Practice of Constraint …, 2017
222017
Applications of MaxSAT in data analysis
OJ Berg, AJ Hyttinen, MJ Järvisalo
Proceedings of Pragmatics of SAT 2015 and 2018, 2019
212019
Causal discovery for linear cyclic models with latent variables
A Hyttinen, F Eberhardt, PO Hoyer
Fifth European Workshop on Probabilistic Graphical Models (PGM-2010), 2010
21*2010
Identifying causal effects via context-specific independence relations
S Tikka, A Hyttinen, J Karvanen
Advances in Neural Information Processing Systems 32, NeurIPS 2019., 2020
172020
Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables
A Hyttinen, F Eberhardt, PO Hoyer
Uncertainty in Artificial Intelligence, 2012
162012
Causal effect identification from multiple incomplete data sources: A general search-based approach
S Tikka, A Hyttinen, J Karvanen
Journal of Statistical Software 99 (5), 2021
132021
A constraint optimization approach to causal discovery from subsampled time series data
A Hyttinen, S Plis, M Järvisalo, F Eberhardt, D Danks
International Journal of Approximate Reasoning 90, 208-225, 2017
122017
Towards Scalable Bayesian Learning of Causal DAGs
J Viinikka, A Hyttinen, J Pensar, M Koivisto
Advances in Neural Information Processing Systems 33, NeurIPS 2020., 2020
112020
A core-guided approach to learning optimal causal graphs
A Hyttinen, P Saikko, M Järvisalo
Proceedings of the 26th International Joint Conference on Artificial …, 2017
112017
Learning chordal Markov networks via branch and bound
K Rantanen, A Hyttinen, M Järvisalo
Advances in neural information processing systems 30, 2017
102017
Noisy-OR Models with Latent Confounding
A Hyttinen, F Eberhardt, PO Hoyer
Uncertainty in Artificial Intelligence, 2011
102011
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Articles 1–20