tag:joss.theoj.org,2005:/papers/tagged/adjointJournal of Open Source Software2024-03-22T13:55:40ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/48192024-03-22T13:55:40Z2024-03-23T00:01:17Zcheckpoint_schedules: schedules for incremental checkpointing of adjoint simulationsacceptedv1.0.02023-09-28 08:06:01 UTC952024-03-22 13:55:40 UTC920246148DaianeI.DolciDepartment of Mathematics, Imperial College London, London, United Kingdom.0000-0002-1435-9538JamesR.MaddisonSchool of Mathematics and Maxwell Institute for Mathematical Sciences, The University of Edinburgh, United Kingdom.0000-0001-5742-4363DavidA.HamDepartment of Mathematics, Imperial College London, London, United Kingdom.0000-0001-9545-9110GuillaumePallezInria, University of Rennes, Rennes, France.0000-0001-8862-3277JulienHerrmannCNRS, IRIT, Université de Toulouse, Toulouse, France.0000-0003-4935-236810.21105/joss.06148https://doi.org/10.5281/zenodo.10817312Pythonhttps://joss.theoj.org/papers/10.21105/joss.06148.pdfCheckpointing methods, Adjoint-based gradienttag:joss.theoj.org,2005:Paper/37462023-03-07T15:25:08Z2023-03-25T13:11:37ZSICOPOLIS-AD v2: tangent linear and adjoint modeling framework for ice sheet modeling enabled by automatic differentiation tool TapenadeacceptedSICOPOLIS-AD v2 (SICOPOLIS v_5.3) 2022-07-27 23:17:07 UTC832023-03-07 15:25:08 UTC820234679ShreyasSunilGaikwadOden Institute for Computational Engineering and Sciences, University of Texas at Austin, USA0000-0003-2079-4218LaurentHascoetInstitut National de Recherche en Informatique et Automatique, France0000-0002-5361-0713SriHari KrishnaNarayananMathematics and Computer Science Division, Argonne National Laboratory, USA0000-0003-0388-5943LizCurry-LoganOden Institute for Computational Engineering and Sciences, University of Texas at Austin, USARalfGreveInstitute of Low Temperature Science, Hokkaido University, Japan, Arctic Research Center, Hokkaido University, Japan0000-0002-1341-4777PatrickHeimbachOden Institute for Computational Engineering and Sciences, University of Texas at Austin, USA, Jackson School of Geosciences, University of Texas at Austin, USA, Institute for Geophysics, University of Texas at Austin, USA0000-0003-3925-616110.21105/joss.04679https://doi.org/10.5281/zenodo.7648249C, Fortran, Pythonhttps://joss.theoj.org/papers/10.21105/joss.04679.pdfSICOPOLIS-AD, Automatic Differentiation, Inverse modeling, Data assimilationtag:joss.theoj.org,2005:Paper/18152021-01-28T22:09:00Z2021-02-15T11:30:23ZGeoBO: Python package for Multi-Objective Bayesian Optimisation and Joint Inversion in Geosciencesacceptedv1.0.02020-07-02 07:04:25 UTC572021-01-28 22:09:00 UTC620212690SebastianHaanSydney Informatics Hub, The University of Sydney, Australia0000-0002-5994-563710.21105/joss.02690https://doi.org/10.5281/zenodo.4451474Pythonhttps://joss.theoj.org/papers/10.21105/joss.02690.pdfGeoscience, Bayesian Optimisation, Inversion, Gaussian Processestag:joss.theoj.org,2005:Paper/7662019-06-18T11:45:46Z2021-02-15T11:32:42Zdolfin-adjoint 2018.1: automated adjoints for FEniCS and Firedrakeaccepted2018.12018-12-31 16:39:19 UTC382019-06-18 11:45:46 UTC420191292SebastianK.MituschSimula Research Laboratory0000-0002-8888-6568SimonW.FunkeSimula Research Laboratory0000-0003-4709-8415JørgenS.DokkenSimula Research Laboratory0000-0001-6489-885810.21105/joss.01292https://doi.org/10.5281/zenodo.3247690Python, GLSLhttps://joss.theoj.org/papers/10.21105/joss.01292.pdffinite element method, optimization, adjoint, gradients, partial differential equationstag:joss.theoj.org,2005:Paper/6052018-10-23T19:00:50Z2021-02-15T11:33:03ZhIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problemsaccepted2.1.02018-08-27 16:51:19 UTC302018-10-23 19:00:50 UTC32018940UmbertoVillaInstitute for Computational Engineering & Sciences, The University of Texas at AustinNoemiPetraApplied Mathematics, School of Natural Sciences, University of California, MercedOmarGhattasInstitute for Computational Engineering & Sciences, Department of Mechanical Engineering, and Department of Geological Sciences, The University of Texas at Austin10.21105/joss.00940https://doi.org/10.5281/zenodo.596931Python, C++, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.00940.pdfInfinite-dimensional inverse problems, adjoint-based methods, numerical optimization, Bayesian inference, uncertainty quantification, PDE toolkittag:joss.theoj.org,2005:Paper/1782017-05-31T00:00:00Z2021-02-15T11:34:11Zcbcbeat: an adjoint-enabled framework for computational cardiac electrophysiologyacceptedv1.02017-04-03 11:52:44 UTC132017-05-31 00:00:00 UTC22017224MarieE.RognesSimula Research Laboratory0000-0002-6872-3710PatrickE.FarrellUniversity of OxfordSimonW.FunkeSimula Research Laboratory0000-0003-4709-8415JohanE.HakeSki videregående skole0000-0002-4042-0128MollyM. c.MaleckarAllen Institute of Cell Science0000-0002-7012-385310.21105/joss.00224https://doi.org/10.5281/zenodo.801552https://joss.theoj.org/papers/10.21105/joss.00224.pdffinite element method, cardiac electrophysiology, adjoint