Bayesian Discovery of Linear Acyclic Causal Models. - Patrik O. Hoyer; Antti Hyttinen (UAI, 2009)

Noisy-OR Models with Latent Confounding. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (UAI, 2011)

Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (UAI, 2012)

Learning linear cyclic causal models with latent variables. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (J. Mach. Learn. Res., 2012)

Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. - Antti Hyttinen; Patrik O. Hoyer; Frederick Eberhardt; Matti Järvisalo (UAI, 2013)

Experiment selection for causal discovery. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (J. Mach. Learn. Res., 2013)

Discovering Causal Relations in the Presence of Latent Confounders. - Antti Hyttinen (2013)

Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming. - Antti Hyttinen; Frederick Eberhardt; Matti Järvisalo (UAI, 2014)

Do-calculus when the True Graph Is Unknown. - Antti Hyttinen; Frederick Eberhardt; Matti Järvisalo (UAI, 2015)

Learning Optimal Chain Graphs with Answer Set Programming. - Dag Sonntag; Matti Järvisalo; José M. Peña 001; Antti Hyttinen (UAI, 2015)

Causal Discovery from Subsampled Time Series Data by Constraint Optimization. - Antti Hyttinen; Sergey M. Plis; Matti Järvisalo; Frederick Eberhardt; David Danks (Probabilistic Graphical Models, 2016)

Advanced Methodologies for Bayesian Networks 2017: Preface. - Joe Suzuki; Antti Hyttinen; Brandon M. Malone (AMBN, 2017)

Reduced Cost Fixing in MaxSAT. - Fahiem Bacchus; Antti Hyttinen; Matti Järvisalo; Paul Saikko (CP, 2017)

A Core-Guided Approach to Learning Optimal Causal Graphs. - Antti Hyttinen; Paul Saikko; Matti Järvisalo (IJCAI, 2017)

Learning Chordal Markov Networks via Branch and Bound. - Kari Rantanen; Antti Hyttinen; Matti Järvisalo (NIPS, 2017)

A constraint optimization approach to causal discovery from subsampled time series data. - Antti Hyttinen; Sergey M. Plis; Matti Järvisalo; Frederick Eberhardt; David Danks (Int. J. Approx. Reason., 2017)

Reduced Cost Fixing for Maximum Satisfiability. - Fahiem Bacchus; Antti Hyttinen; Matti Järvisalo; Paul Saikko (IJCAI, 2018)

Structure Learning for Bayesian Networks over Labeled DAGs. - Antti Hyttinen; Johan Pensar; Juha Kontinen; Jukka Corander (PGM, 2018)

Learning Optimal Causal Graphs with Exact Search. - Kari Rantanen; Antti Hyttinen; Matti Järvisalo (PGM, 2018)

Applications of MaxSAT in Data Analysis. - Jeremias Berg; Antti Hyttinen; Matti Järvisalo (POS@SAT, 2018)

Identifying Causal Effects via Context-specific Independence Relations. - Santtu Tikka; Antti Hyttinen; Juha Karvanen (NeurIPS, 2019)

A logical approach to context-specific independence. - Jukka Corander; Antti Hyttinen; Juha Kontinen; Johan Pensar; Jouko Väänänen (Ann. Pure Appl. Log., 2019)

A Bayesian Approach for Estimating Causal Effects from Observational Data. - Johan Pensar; Topi Talvitie; Antti Hyttinen; Mikko Koivisto (AAAI, 2020)

Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach. - Riku Laine; Antti Hyttinen; Michael Mathioudakis (DS, 2020)

Learning Chordal Markov Networks via Stochastic Local Search. - Kari Rantanen; Antti Hyttinen; Matti Järvisalo (ECAI, 2020)

Towards Scalable Bayesian Learning of Causal DAGs. - Jussi Viinikka; Antti Hyttinen; Johan Pensar; Mikko Koivisto (NeurIPS, 2020)

Learning Optimal Cyclic Causal Graphs from Interventional Data. - Kari Rantanen; Antti Hyttinen; Matti Järvisalo (PGM, 2020)

Discovering causal graphs with cycles and latent confounders: An exact branch-and-bound approach. - Kari Rantanen; Antti Hyttinen; Matti Järvisalo (Int. J. Approx. Reason., 2020)

Maximal ancestral graph structure learning via exact search. - Kari Rantanen; Antti Hyttinen; Matti Järvisalo (UAI, 2021)

Binary Independent Component Analysis via Non-stationarity. - Antti Hyttinen; Vitória Barin Pacela; Aapo Hyvärinen (CoRR, 2021)

Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach. - Santtu Tikka; Antti Hyttinen; Juha Karvanen (J. Stat. Softw., 2021)

A Hardware Perspective to Evaluating Probabilistic Circuits. - Jelin Leslin; Antti Hyttinen; Karthekeyan Periasamy; Lingyun Yao; Martin Trapp 001; Martin Andraud (PGM, 2022)

Binary independent component analysis: a non-stationarity-based approach. - Antti Hyttinen; Vitória Barin Pacela; Aapo Hyvärinen (UAI, 2022)