Bayesian Optimal Experimental Design for Inferring Causal Structure
暂无分享,去创建一个
[1] Gregory F. Cooper,et al. Causal Discovery from a Mixture of Experimental and Observational Data , 1999, UAI.
[2] Daphne Koller,et al. Active Learning for Structure in Bayesian Networks , 2001, IJCAI.
[3] Joris M. Mooij,et al. Cyclic Causal Discovery from Continuous Equilibrium Data , 2013, UAI.
[4] Kevin Murphy,et al. Active Learning of Causal Bayes Net Structure , 2006 .
[5] J. York,et al. Bayesian Graphical Models for Discrete Data , 1995 .
[6] Alain Hauser,et al. Two Optimal Strategies for Active Learning of Causal Models from Interventions , 2012, ArXiv.
[7] D. Madigan,et al. A characterization of Markov equivalence classes for acyclic digraphs , 1997 .
[8] David Maxwell Chickering,et al. Learning Equivalence Classes of Bayesian Network Structures , 1996, UAI.
[9] Mark Craven,et al. A review of active learning approaches to experimental design for uncovering biological networks , 2017, PLoS Comput. Biol..
[10] Kevin P. Murphy,et al. Bayesian structure learning using dynamic programming and MCMC , 2007, UAI.
[11] Mikko Koivisto,et al. Advances in Exact Bayesian Structure Discovery in Bayesian Networks , 2006, UAI.
[12] Judea Pearl,et al. Equivalence and Synthesis of Causal Models , 1990, UAI.
[13] Judea Pearl,et al. Probabilistic reasoning in intelligent systems , 1988 .
[14] Tom Burr,et al. Causation, Prediction, and Search , 2003, Technometrics.
[15] Olga Vitek,et al. A Bayesian Active Learning Experimental Design for Inferring Signaling Networks , 2017, RECOMB.
[16] Tze-Yun Leong,et al. Active Learning for Causal Bayesian Network Structure with Non-symmetrical Entropy , 2009, PAKDD.
[17] Christopher Meek,et al. Strong completeness and faithfulness in Bayesian networks , 1995, UAI.
[18] Bernhard Schölkopf,et al. Identifiability of Causal Graphs using Functional Models , 2011, UAI.
[19] Radhakrishnan Nagarajan,et al. Bayesian Networks in R: with Applications in Systems Biology , 2013 .
[20] Lorenz Wernisch,et al. Reconstruction of gene networks using Bayesian learning and manipulation experiments , 2004, Bioinform..
[21] Jeffrey W. Miller. A detailed treatment of Doob's theorem , 2018, 1801.03122.
[22] Yangbo He,et al. Active Learning of Causal Networks with Intervention Experiments and Optimal Designs , 2008 .
[23] Nir Friedman,et al. Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks , 2004, Machine Learning.
[24] Frederick Eberhardt,et al. Almost Optimal Intervention Sets for Causal Discovery , 2008, UAI.
[25] Bonnie Berger,et al. Reconstructing Causal Biological Networks through Active Learning , 2016, PloS one.
[26] Christine B Peterson,et al. Bayesian Inference of Multiple Gaussian Graphical Models , 2015, Journal of the American Statistical Association.
[27] Mikko Koivisto,et al. Exact Bayesian Structure Discovery in Bayesian Networks , 2004, J. Mach. Learn. Res..
[28] K. Sachs,et al. Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data , 2005, Science.
[29] David Maxwell Chickering,et al. Learning Bayesian Networks: The Combination of Knowledge and Statistical Data , 1994, Machine Learning.
[30] Anthony Almudevar,et al. Using a Bayesian Posterior Density in the Design of Perturbation Experiments for Network Reconstruction , 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.
[31] Wray L. Buntine. Theory Refinement on Bayesian Networks , 1991, UAI.
[32] Qiang Shen,et al. Learning Bayesian networks: approaches and issues , 2011, The Knowledge Engineering Review.
[33] J. Pearl. Causality: Models, Reasoning and Inference , 2000 .
[34] Peter Bühlmann,et al. Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs (Abstract) , 2011, UAI.
[35] Kevin P. Murphy,et al. Exact Bayesian structure learning from uncertain interventions , 2007, AISTATS.
[36] Marco Scutari,et al. Learning Bayesian Networks with the bnlearn R Package , 2009, 0908.3817.
[37] Marco L. Della Vedova,et al. Learning Markov Equivalence Classes of Directed Acyclic Graphs: An Objective Bayes Approach , 2018, Bayesian Analysis.