tag:joss.theoj.org,2005:/papers/tagged/Probabilistic%20ModellingJournal of Open Source Software2023-10-03T09:14:22ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/46202023-10-03T09:14:22Z2023-10-12T14:13:09ZTensorInference: A Julia package for tensor-based probabilistic inferenceaccepted0.2.02023-07-22 22:27:34 UTC902023-10-03 09:14:22 UTC820235700MartinRoa-VillescasEindhoven University of Technology0009-0009-0291-503XJin-GuoLiuHong Kong University of Science and Technology (Guangzhou)0000-0003-1635-267910.21105/joss.05700https://doi.org/10.5281/zenodo.8399580Juliahttps://joss.theoj.org/papers/10.21105/joss.05700.pdfprobabilistic graphical models, tensor networks, probabilistic inferencetag:joss.theoj.org,2005:Paper/43142023-06-21T01:25:57Z2023-06-24T19:34:40ZPyVBMC: Efficient Bayesian inference in Pythonacceptedv1.0.02023-03-16 14:20:45 UTC862023-06-21 01:25:57 UTC820235428BobbyHugginsUniversity of Helsinki0009-0006-3475-5964ChengkunLiUniversity of Helsinki0000-0001-5848-910XMarlonTobabenUniversity of Helsinki0000-0002-9778-0853MikkoJ.AarnosUniversity of HelsinkiLuigiAcerbiUniversity of Helsinki0000-0001-7471-733610.21105/joss.05428https://doi.org/10.5281/zenodo.7966315Pythonhttps://joss.theoj.org/papers/10.21105/joss.05428.pdfBayesian statistics, Bayesian inference, Probabilistic programming, Model evidence, Machine learning, Simulator-based inferencetag:joss.theoj.org,2005:Paper/35222022-08-12T21:53:58Z2022-08-15T19:37:10ZGenerative DAGs as an Interface Into Probabilistic Programming with the R Package causactacceptedv0.4.12022-04-27 21:11:31 UTC762022-08-12 21:53:58 UTC720224415AdamJ.FleischhackerAdam Fleischhacker, JP Morgan Chase Faculty Fellow, University of Delaware, Newark, DE 197160000-0003-2871-4788ThiHong NhungNguyenInstitute for Financial Services Analytics, University of Delaware, Newark, DE 1971610.21105/joss.04415https://doi.org/10.5281/zenodo.6949489Rhttps://joss.theoj.org/papers/10.21105/joss.04415.pdfBayesian inference, probabilistic programming, graphical models, directed acyclic graphstag:joss.theoj.org,2005:Paper/27472021-07-17T16:42:20Z2021-07-18T00:02:32ZLumen: A software for the interactive visualization of probabilistic models together with dataacceptedv0.92021-06-10 11:24:03 UTC632021-07-17 16:42:20 UTC620213395PhilippLucasInstitute of Data Science, German Aerospace Center0000-0002-6687-8209JoachimGiesenFriedrich-Schiller-University Jena10.21105/joss.03395https://doi.org/10.5281/zenodo.5069308JavaScripthttps://joss.theoj.org/papers/10.21105/joss.03395.pdfProbabilistic Modelling, Model Criticism, Model Validation, Model Understanding, Visual-Interactive Exploration, Web-Interfacetag:joss.theoj.org,2005:Paper/23702021-05-13T13:58:56Z2021-05-14T00:01:48ZPyGModels: A Python package for exploring Probabilistic Graphical Models with Graph Theoretical Structuresacceptedv0.1.0-beta2021-02-03 01:09:56 UTC612021-05-13 13:58:56 UTC620213115DoğuKaanEraslanÉcole Pratique des Hautes Études, Université PSL, Paris, France0000-0002-1552-893810.21105/joss.03115https://doi.org/10.5281/zenodo.4751740Pythonhttps://joss.theoj.org/papers/10.21105/joss.03115.pdfprobabilistic graphical models, Bayesian statistics, Probabilistic inferencetag:joss.theoj.org,2005:Paper/19072021-02-05T18:18:40Z2021-02-15T11:30:13ZPyAutoFit: A Classy Probabilistic Programming Language for Model Composition and Fittingacceptedv0.64.32020-07-24 09:45:21 UTC582021-02-05 18:18:40 UTC620212550James.W.NightingaleInstitute for Computational Cosmology, Stockton Rd, Durham, United Kingdom, DH1 3LE0000-0002-8987-7401RichardG.HayesInstitute for Computational Cosmology, Stockton Rd, Durham, United Kingdom, DH1 3LEMatthewGriffithsConcR Ltd, London, UK0000-0002-2553-244710.21105/joss.02550https://doi.org/10.5281/zenodo.4497861Pythonhttps://joss.theoj.org/papers/10.21105/joss.02550.pdfstatistics, Bayesian inference, probabilistic programming, model fitting