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Antti Hyttinen
Antti Hyttinen
Silo AI
Verified email at alumni.helsinki.fi - Homepage
Title
Cited by
Cited by
Year
Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming.
A Hyttinen, F Eberhardt, M Järvisalo
UAI, 340-349, 2014
1482014
Learning Linear Cyclic Causal Models with Latent Variables
A Hyttinen, F Eberhardt, PO Hoyer
Journal of Machine Learning Research 13, 3387-3439, 2012
1382012
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
1122013
Experiment selection for causal discovery
A Hyttinen, F Eberhardt, PO Hoyer
The Journal of Machine Learning Research 14 (1), 3041-3071, 2013
1072013
Do-calculus when the True Graph Is Unknown.
A Hyttinen, F Eberhardt, M Järvisalo
UAI, 395-404, 2015
572015
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
432016
Bayesian discovery of linear acyclic causal models
PO Hoyer, A Hyttinen
Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence …, 2009
372009
Identifying causal effects via context-specific independence relations
S Tikka, A Hyttinen, J Karvanen
Advances in Neural Information Processing Systems 32, NeurIPS 2019., 2020
342020
Reduced cost fixing in MaxSAT
F Bacchus, A Hyttinen, M Järvisalo, P Saikko
International Conference on Principles and Practice of Constraint …, 2017
342017
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
332019
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
292020
Applications of MaxSAT in data analysis
J Berg, A Hyttinen, M Järvisalo
Pragmatics of SAT, 2015
292015
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
272021
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
242015
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
24*2010
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
222017
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
192012
A Core-Guided Approach to Learning Optimal Causal Graphs.
A Hyttinen, P Saikko, M Järvisalo
IJCAI, 645-651, 2017
182017
Discovering causal graphs with cycles and latent confounders: An exact branch-and-bound approach
K Rantanen, A Hyttinen, M Järvisalo
International Journal of Approximate Reasoning 117, 29-49, 2020
152020
Do-search: a tool for causal inference and study design with multiple data sources
J Karvanen, S Tikka, A Hyttinen
Epidemiology 32 (1), 111-119, 2021
142021
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