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Journal Abstract Search

308 related items for PubMed ID: 30793299

  • 21. Missing data in amortized simulation-based neural posterior estimation.
    Wang Z, Hasenauer J, Schälte Y.
    PLoS Comput Biol; 2024 Jun; 20(6):e1012184. PubMed ID: 38885265
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  • 22. Training deep neural density estimators to identify mechanistic models of neural dynamics.
    Gonçalves PJ, Lueckmann JM, Deistler M, Nonnenmacher M, Öcal K, Bassetto G, Chintaluri C, Podlaski WF, Haddad SA, Vogels TP, Greenberg DS, Macke JH.
    Elife; 2020 Sep 17; 9():. PubMed ID: 32940606
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  • 23. Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study.
    Saulnier E, Gascuel O, Alizon S.
    PLoS Comput Biol; 2017 Mar 17; 13(3):e1005416. PubMed ID: 28263987
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  • 24. Extending approximate Bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest.
    Collin FD, Durif G, Raynal L, Lombaert E, Gautier M, Vitalis R, Marin JM, Estoup A.
    Mol Ecol Resour; 2021 Nov 17; 21(8):2598-2613. PubMed ID: 33950563
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  • 25. Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation.
    AKesson M, Singh P, Wrede F, Hellander A.
    IEEE/ACM Trans Comput Biol Bioinform; 2022 Nov 17; 19(6):3353-3365. PubMed ID: 34460381
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  • 26. Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong.
    Thompson A, Liebeskind BJ, Scully EJ, Landis MJ.
    Syst Biol; 2024 May 27; 73(1):183-206. PubMed ID: 38189575
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  • 27. Expectation propagation with factorizing distributions: a Gaussian approximation and performance results for simple models.
    Ribeiro F, Opper M.
    Neural Comput; 2011 Apr 27; 23(4):1047-69. PubMed ID: 21222527
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  • 28. Fundamentals and Recent Developments in Approximate Bayesian Computation.
    Lintusaari J, Gutmann MU, Dutta R, Kaski S, Corander J.
    Syst Biol; 2017 Jan 01; 66(1):e66-e82. PubMed ID: 28175922
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  • 29. ABC random forests for Bayesian parameter inference.
    Raynal L, Marin JM, Pudlo P, Ribatet M, Robert CP, Estoup A.
    Bioinformatics; 2019 May 15; 35(10):1720-1728. PubMed ID: 30321307
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  • 30. Approximate maximum likelihood estimation for population genetic inference.
    Bertl J, Ewing G, Kosiol C, Futschik A.
    Stat Appl Genet Mol Biol; 2017 Nov 27; 16(5-6):387-405. PubMed ID: 29095700
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  • 31. Optimizing threshold-schedules for sequential approximate Bayesian computation: applications to molecular systems.
    Silk D, Filippi S, Stumpf MP.
    Stat Appl Genet Mol Biol; 2013 Oct 01; 12(5):603-18. PubMed ID: 24025688
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  • 32. A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks.
    Mariño IP, Zaikin A, Míguez J.
    PLoS One; 2017 Oct 01; 12(8):e0182015. PubMed ID: 28797087
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  • 33. ABCtoolbox: a versatile toolkit for approximate Bayesian computations.
    Wegmann D, Leuenberger C, Neuenschwander S, Excoffier L.
    BMC Bioinformatics; 2010 Mar 04; 11():116. PubMed ID: 20202215
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  • 34. Inferring Rates and Length-Distributions of Indels Using Approximate Bayesian Computation.
    Levy Karin E, Shkedy D, Ashkenazy H, Cartwright RA, Pupko T.
    Genome Biol Evol; 2017 May 01; 9(5):1280-1294. PubMed ID: 28453624
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  • 35. Bayesian graph convolutional network with partial observations.
    Luo S, Liu P, Ye X.
    PLoS One; 2024 May 01; 19(7):e0307146. PubMed ID: 39024246
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  • 36. Reliable ABC model choice via random forests.
    Pudlo P, Marin JM, Estoup A, Cornuet JM, Gautier M, Robert CP.
    Bioinformatics; 2016 Mar 15; 32(6):859-66. PubMed ID: 26589278
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  • 37. Approximate Bayesian computation.
    Sunnåker M, Busetto AG, Numminen E, Corander J, Foll M, Dessimoz C.
    PLoS Comput Biol; 2013 Mar 15; 9(1):e1002803. PubMed ID: 23341757
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  • 38. The metabolic network of Clostridium acetobutylicum: Comparison of the approximate Bayesian computation via sequential Monte Carlo (ABC-SMC) and profile likelihood estimation (PLE) methods for determinability analysis.
    Thorn GJ, King JR.
    Math Biosci; 2016 Jan 15; 271():62-79. PubMed ID: 26561777
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  • 39. Variational Bayesian mixture model on a subspace of exponential family distributions.
    Watanabe K, Akaho S, Omachi S, Okada M.
    IEEE Trans Neural Netw; 2009 Nov 15; 20(11):1783-96. PubMed ID: 19770092
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  • 40. Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach.
    Koutroumpas K, Ballarini P, Votsi I, Cournède PH.
    Bioinformatics; 2016 Sep 01; 32(17):i781-i789. PubMed ID: 27587701
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