tag:joss.theoj.org,2005:/papers/tagged/stochasticsJournal of Open Source Software2023-11-05T15:58:05ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/42122023-11-05T15:58:05Z2023-11-06T00:00:26ZSuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in Racceptedv1.0.02023-02-15 18:37:21 UTC912023-11-05 15:58:05 UTC820235422DavidMcCoyDepartment of Biostatistics, University of California Berkeley, Berkeley, CA 94704, U.S.A.0000-0002-5515-6307AlejandroSchulerDepartment of Biostatistics, University of California Berkeley, Berkeley, CA 94704, U.S.A.0000-0003-4853-6130AlanHubbardDepartment of Biostatistics, University of California Berkeley, Berkeley, CA 94704, U.S.A.0000-0002-3769-0127Markvan der LaanDepartment of Biostatistics, University of California Berkeley, Berkeley, CA 94704, U.S.A.0000-0003-1432-551110.21105/joss.05422https://doi.org/10.5281/zenodo.10038794Rhttps://joss.theoj.org/papers/10.21105/joss.05422.pdfcausal inference, machine learning, stochastic interventions, efficient estimation, targeted learning, mixed exposurestag:joss.theoj.org,2005:Paper/45242023-09-26T10:32:27Z2023-10-24T13:30:07ZBernadette: Bayesian Inference and Model Selection for Stochastic Epidemics in Racceptedv.1.1.42023-06-04 21:22:05 UTC892023-09-26 10:32:27 UTC820235612LamprosBouranisDepartment of Statistics, Athens University of Economics and Business, Athens, Greece0000-0002-1291-219210.21105/joss.05612https://doi.org/10.5281/zenodo.8376673R, C++, Stanhttps://joss.theoj.org/papers/10.21105/joss.05612.pdfBayesian, Epidemicstag:joss.theoj.org,2005:Paper/45182023-09-25T17:53:00Z2023-09-26T00:01:08ZMacroModelling.jl: A Julia package for developing and solving dynamic stochastic general equilibrium modelsacceptedv.0.1.232023-06-01 16:00:32 UTC892023-09-25 17:53:00 UTC820235598ThoreKockerolsNorges Bank, Norway0000-0002-0068-180910.21105/joss.05598https://doi.org/10.5281/zenodo.8374466Juliahttps://joss.theoj.org/papers/10.21105/joss.05598.pdfDSGE, macroeconomics, perturbation, difference equations, dynamical systemstag:joss.theoj.org,2005:Paper/40212023-03-09T10:43:20Z2023-03-10T00:04:42ZFast and flexible simulation and parameter estimation for synthetic biology using bioscrapeacceptedv1.22022-11-23 08:27:41 UTC832023-03-09 10:43:20 UTC820235057AyushPandeyControl and Dynamical Systems, California Institute of Technology, Pasadena, CA, USA0000-0003-3590-4459WilliamPooleAltos Labs, San Francisco, CA, USA0000-0002-2958-6776AnandhSwaminathanGhost Locomotion, Mountain View, CA, USA0000-0001-9935-6530VictoriaHsiaoAmyris, Emeryville, CA, USA0000-0001-9297-1522RichardM.MurrayControl and Dynamical Systems and Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA0000-0002-5785-748110.21105/joss.05057https://doi.org/10.5281/zenodo.7677726Python, Cython, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05057.pdfsynthetic biology, systems biology, deterministic and stochastic simulations, parameter inferencetag:joss.theoj.org,2005:Paper/40182023-03-07T14:18:54Z2023-03-08T00:04:15ZDistributedSparseGrids.jl: A Julia library implementing an Adaptive Sparse Grid collocation methodaccepted0.1.32022-11-22 10:27:43 UTC832023-03-07 14:18:54 UTC820235003MaximilianBittensFederal Institute for Geosciences and Natural Resources (BGR), Germany0000-0001-9954-294XRobertL.GatesIndependent Researcher, Germany10.21105/joss.05003https://doi.org/10.5281/zenodo.7673697Juliahttps://joss.theoj.org/papers/10.21105/joss.05003.pdfstochastics, sparse grids, high-performance computingtag:joss.theoj.org,2005:Paper/34202022-12-08T21:58:29Z2022-12-09T03:31:51ZPyNM: a Lightweight Python implementation of Normative Modelingaccepted1.0.0b12022-03-11 18:20:42 UTC802022-12-08 21:58:29 UTC720224321AnnabelleHarveyCentre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Université de Montréal, QC, Canada, Centre de Recherche du CHU Sainte-Justine, Université de Montréal, QC, Canada0000-0002-9940-8799GuillaumeDumasCentre de Recherche du CHU Sainte-Justine, Université de Montréal, QC, Canada, Mila - Quebec AI Institute, Université de Montréal, QC, Canada0000-0002-2253-184410.21105/joss.04321https://doi.org/10.5281/zenodo.7396721Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.04321.pdfNormative Modeling, Heterogeneity, Heteroskedasticity, Big Data, Centiles, LOESS, Gaussian Process, Stochastic Variational Gaussian Process, GAMLSS, Computational Psychiatry, Neurosciencetag:joss.theoj.org,2005:Paper/31512022-07-04T16:37:30Z2022-07-05T00:00:36ZNeuralFieldEq.jl: A flexible solver to compute Neural Field Equations in several scenariosacceptedv0.1.22021-11-02 22:16:16 UTC752022-07-04 16:37:30 UTC720223974TiagoSequeiraInstituto Superior Técnico - University of Lisbon0000-0001-8579-367610.21105/joss.03974https://doi.org/10.5281/zenodo.6226695Juliahttps://joss.theoj.org/papers/10.21105/joss.03974.pdfComputational Neuroscience, Neural Field Equations, Stochastic Processes, Delayed Equations, Fast Fourier Transformstag:joss.theoj.org,2005:Paper/33002022-06-03T18:51:07Z2022-06-04T00:01:02ZpySBeLT: A Python software package for stochastic sediment transport under rarefied conditionsacceptedv1.0.02022-01-21 07:40:00 UTC742022-06-03 18:51:07 UTC720224282SarahZwiepSchool of Environmental Science, Simon Fraser University0000-0002-0812-9509ShawnM.ChartrandSchool of Environmental Science, Simon Fraser University, Department of Earth Sciences, Simon Fraser University0000-0002-9309-113710.21105/joss.04282https://doi.org/10.6084/m9.figshare.19967552.v3Pythonhttps://joss.theoj.org/papers/10.21105/joss.04282.pdfgeomorphology, sediment transport, stochastic, Poissontag:joss.theoj.org,2005:Paper/34062022-05-26T04:16:44Z2022-05-27T00:00:59ZVTUFileHandler: A VTU library in the Julia language that implements an algebra for basic mathematical operations on VTU dataaccepted0.1.32022-03-01 13:44:50 UTC732022-05-26 04:16:44 UTC720224300MaximilianBittensFederal Institute for Geosciences and Natural Resources (BGR)0000-0001-9954-294X10.21105/joss.04300https://doi.org/10.5281/zenodo.6576155Juliahttps://joss.theoj.org/papers/10.21105/joss.04300.pdfVTK unstructered grid, Stochastic/parametric post-processing of simulation resultstag:joss.theoj.org,2005:Paper/32932022-04-18T15:53:10Z2022-04-19T00:00:54ZSGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithmsaccepted0.2.92022-01-17 18:25:10 UTC722022-04-18 15:53:10 UTC720224113JeremieCoullonCervest, London, UK0000-0002-7032-3425ChristopherNemethLancaster University, UK0000-0002-9084-386610.21105/joss.04113https://doi.org/10.5281/zenodo.6460681Pythonhttps://joss.theoj.org/papers/10.21105/joss.04113.pdfJAX, MCMC, SGMCMC, Bayesian inference