Antti Hyttinen

44 papers A* 5A 11B 1C 1Journal 15Unranked 8

Year	Rank	Type	Title / Venue / Authors
2022	—	`conf`	A Hardware Perspective to Evaluating Probabilistic Circuits. PGM Jelin Leslin, Antti Hyttinen, Karthekeyan Periasamy, Lingyun Yao, Martin Trapp, Martin Andraud
2022	A	`conf`	Binary independent component analysis: a non-stationarity-based approach. UAI Antti Hyttinen, Vitória Barin Pacela, Aapo Hyvärinen
2021	J	`jnl`	Binary Independent Component Analysis via Non-stationarity. CoRR Antti Hyttinen, Vitória Barin Pacela, Aapo Hyvärinen
2021	J	`jnl`	Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach. J. Stat. Softw. Santtu Tikka, Antti Hyttinen, Juha Karvanen
2021	A	`conf`	Maximal ancestral graph structure learning via exact search. UAI Kari Rantanen, Antti Hyttinen, Matti Järvisalo
2020	A*	`conf`	A Bayesian Approach for Estimating Causal Effects from Observational Data. AAAI Johan Pensar, Topi Talvitie, Antti Hyttinen, Mikko Koivisto
2020	J	`jnl`	Discovering causal graphs with cycles and latent confounders: An exact branch-and-bound approach. Int. J. Approx. Reason. Kari Rantanen, Antti Hyttinen, Matti Järvisalo
2020	B	`conf`	Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach. DS Riku Laine, Antti Hyttinen, Michael Mathioudakis
2020	J	`jnl`	Identifying Causal Effects via Context-specific Independence Relations. CoRR Santtu Tikka, Antti Hyttinen, Juha Karvanen
2020	A	`conf`	Learning Chordal Markov Networks via Stochastic Local Search. ECAI Kari Rantanen, Antti Hyttinen, Matti Järvisalo
2020	—	`conf`	Learning Optimal Cyclic Causal Graphs from Interventional Data. PGM Kari Rantanen, Antti Hyttinen, Matti Järvisalo
2020	A*	`conf`	Towards Scalable Bayesian Learning of Causal DAGs. NeurIPS Jussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto
2020	J	`jnl`	Towards Scalable Bayesian Learning of Causal DAGs. CoRR Jussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto
2019	J	`jnl`	A logical approach to context-specific independence. Ann. Pure Appl. Log. Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen
2019	J	`jnl`	Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach. CoRR Santtu Tikka, Antti Hyttinen, Juha Karvanen
2019	A*	`conf`	Identifying Causal Effects via Context-specific Independence Relations. NeurIPS Santtu Tikka, Antti Hyttinen, Juha Karvanen
2018	—	`conf`	Applications of MaxSAT in Data Analysis. POS@SAT Jeremias Berg, Antti Hyttinen, Matti Järvisalo
2018	—	`conf`	Learning Optimal Causal Graphs with Exact Search. PGM Kari Rantanen, Antti Hyttinen, Matti Järvisalo
2018	A*	`conf`	Reduced Cost Fixing for Maximum Satisfiability. IJCAI Fahiem Bacchus, Antti Hyttinen, Matti Järvisalo, Paul Saikko
2018	—	`conf`	Structure Learning for Bayesian Networks over Labeled DAGs. PGM Antti Hyttinen, Johan Pensar, Juha Kontinen, Jukka Corander
2017	A*	`conf`	A Core-Guided Approach to Learning Optimal Causal Graphs. IJCAI Antti Hyttinen, Paul Saikko, Matti Järvisalo
2017	J	`jnl`	A constraint optimization approach to causal discovery from subsampled time series data. Int. J. Approx. Reason. Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
2017	—	`conf`	Advanced Methodologies for Bayesian Networks 2017: Preface. AMBN Joe Suzuki, Antti Hyttinen, Brandon M. Malone
2017	—	`conf`	Learning Chordal Markov Networks via Branch and Bound. NIPS Kari Rantanen, Antti Hyttinen, Matti Järvisalo
2017	—	`ed.`	Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2017, Kyoto, Japan, September 20-22, 2017 AMBN Antti Hyttinen, Joe Suzuki, Brandon M. Malone
2017	A	`conf`	Reduced Cost Fixing in MaxSAT. CP Fahiem Bacchus, Antti Hyttinen, Matti Järvisalo, Paul Saikko
2016	C	`conf`	A Logical Approach to Context-Specific Independence. WoLLIC Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen
2016	—	`conf`	Causal Discovery from Subsampled Time Series Data by Constraint Optimization. Probabilistic Graphical Models Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
2016	J	`jnl`	Causal Discovery from Subsampled Time Series Data by Constraint Optimization. CoRR Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
2015	A	`conf`	Do-calculus when the True Graph Is Unknown. UAI Antti Hyttinen, Frederick Eberhardt, Matti Järvisalo
2015	A	`conf`	Learning Optimal Chain Graphs with Answer Set Programming. UAI Dag Sonntag, Matti Järvisalo, José M. Peña, Antti Hyttinen
2014	A	`conf`	Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming. UAI Antti Hyttinen, Frederick Eberhardt, Matti Järvisalo
2014	—	`ed.`	Proceedings of the UAI 2014 Workshop Causal Inference: Learning and Prediction co-located with 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), Quebec City, Canada, July 27, 2014. CI@UAI Joris M. Mooij, Dominik Janzing, Jonas Peters, Tom Claassen, Antti Hyttinen
2013	—	`—`	Discovering Causal Relations in the Presence of Latent Confounders. Antti Hyttinen
2013	A	`conf`	Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. UAI Antti Hyttinen, Patrik O. Hoyer, Frederick Eberhardt, Matti Järvisalo
2013	J	`jnl`	Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. CoRR Antti Hyttinen, Patrik O. Hoyer, Frederick Eberhardt, Matti Järvisalo
2013	J	`jnl`	Experiment selection for causal discovery. J. Mach. Learn. Res. Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	J	`jnl`	Bayesian Discovery of Linear Acyclic Causal Models CoRR Patrik O. Hoyer, Antti Hyttinen
2012	J	`jnl`	Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables CoRR Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	A	`conf`	Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables. UAI Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	J	`jnl`	Learning linear cyclic causal models with latent variables. J. Mach. Learn. Res. Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	J	`jnl`	Noisy-OR Models with Latent Confounding CoRR Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2011	A	`conf`	Noisy-OR Models with Latent Confounding. UAI Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2009	A	`conf`	Bayesian Discovery of Linear Acyclic Causal Models. UAI Patrik O. Hoyer, Antti Hyttinen