Name
Playground
About
FAQ
GitHub
Playground
Shortest Path Finder
Community Detector
Connected Papers
Author Trending
Victor E. Brunini
Claudia Calabrese
Hao Mao
Peter Malec
S. Sibi Chakkaravarthy
Naoto Katsumata
Giovanni Venturelli
Chen Ma
Radu Timofte
Kuanrui Yin
Home
/
Author
/
ANTTI HYTTINEN
Author Info
Open Visualization
Name
Affiliation
Papers
ANTTI HYTTINEN
Helsinki Institute for Information Technology, Department of Computer Science, University of Helsinki, Finland
27
Collaborators
Citations
PageRank
25
97
12.55
Referers
Referees
References
154
241
227
Search Limit
100
241
Publications (27 rows)
Collaborators (25 rows)
Referers (100 rows)
Referees (100 rows)
Title
Citations
PageRank
Year
Maximal ancestral graph structure learning via exact search.
0
0.34
2021
Discovering causal graphs with cycles and latent confounders: An exact branch-and-bound approach
0
0.34
2020
Towards Scalable Bayesian Learning of Causal DAGs
0
0.34
2020
Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach
0
0.34
2020
A Bayesian Approach For Estimating Causal Effects From Observational Data
0
0.34
2020
Identifying Causal Effects via Context-specific Independence Relations
0
0.34
2019
Causal Effect Identification From Multiple Incomplete Data Sources: A General Search-Based Approach
0
0.34
2019
Reduced Cost Fixing for Maximum Satisfiability.
1
0.37
2018
Structure Learning for Bayesian Networks over Labeled DAGs.
0
0.34
2018
Learning Optimal Causal Graphs with Exact Search.
0
0.34
2018
Applications of MaxSAT in Data Analysis.
0
0.34
2018
Reduced Cost Fixing In Maxsat
1
0.37
2017
A constraint optimization approach to causal discovery from subsampled time series data.
2
0.40
2017
Advanced Methodologies for Bayesian Networks 2017: Preface.
0
0.34
2017
A Core-Guided Approach to Learning Optimal Causal Graphs.
0
0.34
2017
Learning Chordal Markov Networks via Branch and Bound.
1
0.35
2017
A Logical Approach to Context-Specific Independence.
3
0.39
2016
Causal Discovery from Subsampled Time Series Data by Constraint Optimization.
4
0.45
2016
Do-calculus when the True Graph Is Unknown.
6
0.48
2015
Learning Optimal Chain Graphs with Answer Set Programming
7
0.57
2015
Constraint-Based Causal Discovery: Conflict Resolution With Answer Set Programming
15
0.79
2014
Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure.
16
0.85
2013
Experiment selection for causal discovery
12
1.14
2013
Bayesian discovery of linear acyclic causal models
5
0.43
2012
Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables
4
0.46
2012
Learning linear cyclic causal models with latent variables
15
0.92
2012
Noisy-OR Models with Latent Confounding
5
0.54
2011
1
