tag:joss.theoj.org,2005:/papers/tagged/simulation-based%20inferenceJournal of Open Source Software2023-09-22T03:40:40ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/45702023-09-22T03:40:40Z2023-09-25T08:21:56ZBayesFlow: Amortized Bayesian Workflows With Neural Networksacceptedv1.1.12023-06-27 14:58:24 UTC892023-09-22 03:40:40 UTC820235702StefanT.RadevCluster of Excellence STRUCTURES, Heidelberg University, Germany0000-0002-6702-9559MarvinSchmittCluster of Excellence SimTech, University of Stuttgart, Germany0000-0003-1293-820XLukasSchumacherInstitute for Psychology, Heidelberg University, Germany0000-0003-1512-8288LasseElsemüllerInstitute for Psychology, Heidelberg University, Germany0000-0003-0368-720XValentinPratzVisual Learning Lab, Heidelberg University, Germany0000-0001-8371-3417YannikSchälteLife and Medical Sciences Institute, University of Bonn, Germany0000-0003-1293-820XUllrichKötheVisual Learning Lab, Heidelberg University, Germany0000-0001-6036-1287Paul-ChristianBürknerCluster of Excellence SimTech, University of Stuttgart, Germany, Department of Statistics, TU Dortmund University, Germany0000-0001-5765-899510.21105/joss.05702https://doi.org/10.5281/zenodo.8346393Pythonhttps://joss.theoj.org/papers/10.21105/joss.05702.pdfsimulation-based inference, likelihood-free inference, Bayesian inference, amortized Bayesian 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/32952022-07-19T20:57:39Z2022-07-20T08:38:54Zswyft: Truncated Marginal Neural Ratio Estimation in Pythonacceptedv0.3.02022-01-18 13:06:59 UTC752022-07-19 20:57:39 UTC720224205BenjaminKurtMillerGravitation Astroparticle Physics Amsterdam (GRAPPA), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, Amsterdam Machine Learning Lab (AMLab), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, AI4Science Lab, University of Amsterdam, Science Park 904, 1098 XH Amsterdam0000-0003-0387-8727AlexColeGravitation Astroparticle Physics Amsterdam (GRAPPA), University of Amsterdam, Science Park 904, 1098 XH Amsterdam0000-0001-8035-4308ChristophWenigerGravitation Astroparticle Physics Amsterdam (GRAPPA), University of Amsterdam, Science Park 904, 1098 XH Amsterdam0000-0001-7579-8684FrancescoNattinoNetherlands eScience Center, Science Park 140, 1098 XG Amsterdam, The Netherlands0000-0003-3286-0139OuKuNetherlands eScience Center, Science Park 140, 1098 XG Amsterdam, The Netherlands0000-0002-5373-5209MeiertW.GrootesNetherlands eScience Center, Science Park 140, 1098 XG Amsterdam, The Netherlands0000-0002-5733-479510.21105/joss.04205https://doi.org/10.5281/zenodo.6412465Jupyter Notebook, Pythonhttps://joss.theoj.org/papers/10.21105/joss.04205.pdfsimulation-based inference, likelihood-free inference, machine learning, bayesian inference, system identification, parameter identification, inverse problemtag:joss.theoj.org,2005:Paper/18542020-08-21T10:16:39Z2021-02-15T11:30:16Zsbi: A toolkit for simulation-based inferenceacceptedv0.10.02020-07-14 13:30:40 UTC522020-08-21 10:16:39 UTC520202505AlvaroTejero-CanteroEqually contributing authors, Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich0000-0002-8768-4227JanBoeltsEqually contributing authors, Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich0000-0003-4979-7092MichaelDeistlerEqually contributing authors, Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich0000-0002-3573-0404Jan-MatthisLueckmannEqually contributing authors, Computational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich0000-0003-4320-4663ConorDurkanEqually contributing authors, School of Informatics, University of Edinburgh0000-0001-9333-7777PedroJ.GonçalvesComputational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich, Neural Systems Analysis, Center of Advanced European Studies and Research (caesar), Bonn0000-0002-6987-4836DavidS.GreenbergComputational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich, Model-Driven Machine Learning, Centre for Materials and Coastal Research, Helmholtz-Zentrum Geesthacht0000-0002-8515-0459JakobH.MackeComputational Neuroengineering, Department of Electrical and Computer Engineering, Technical University of Munich, Machine Learning in Science, University of Tübingen, Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen0000-0001-5154-891210.21105/joss.02505https://doi.org/10.5281/zenodo.3993098Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.02505.pdfsimulation science, likelihood-free inference, bayesian inference, system identification, parameter identification