tag:joss.theoj.org,2005:/papers/tagged/differentiationJournal of Open Source Software2024-03-16T22:48:59ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/46292024-03-16T22:48:59Z2024-03-17T00:00:58ZFeenoX: a cloud-first finite-element(ish) computational engineering toolacceptedv0.32023-07-27 16:01:35 UTC952024-03-16 22:48:59 UTC920245846JeremyThelerSeamplex, Argentina, Instituto Balseiro, Argentina0000-0002-4142-498010.21105/joss.05846https://doi.org/10.5281/zenodo.10819606M4, C, GLSLhttps://joss.theoj.org/papers/10.21105/joss.05846.pdfengineering, partial differential equations, differential algebraic equationstag:joss.theoj.org,2005:Paper/46922024-03-01T08:15:12Z2024-03-05T12:14:06ZΦ-ML: Intuitive Scientific Computing with Dimension Types for Jax, PyTorch, TensorFlow & NumPyacceptedv1.0.02023-08-11 11:05:07 UTC952024-03-01 08:15:12 UTC920246171PhilippHollSchool of Computation, Information and Technology, Technical University of Munich, Germany0000-0001-9246-5195NilsThuereySchool of Computation, Information and Technology, Technical University of Munich, Germany0000-0001-6647-891010.21105/joss.06171https://doi.org/10.6084/m9.figshare.25282300Python, C++https://joss.theoj.org/papers/10.21105/joss.06171.pdfMachine Learning, Jax, TensorFlow, PyTorch, NumPy, Differentiable simulations, Sparse linear systems, Preconditionerstag:joss.theoj.org,2005:Paper/30012024-02-29T18:30:52Z2024-03-01T00:00:33ZcppTPSA/pyTPSA: a C++/Python package for truncated power series algebraacceptedv1.0.02021-08-27 20:06:27 UTC942024-02-29 18:30:52 UTC920244818HeZhangThomas Jefferson National Accelerator Facility, Newport News, VA 23606, USA0000-0001-7701-411810.21105/joss.04818https://doi.org/10.5281/zenodo.10728770C++, Pythonhttps://joss.theoj.org/papers/10.21105/joss.04818.pdfdifferential algebra, truncated power series algebra, accelerator physics, astronomy, beam dynamicstag:joss.theoj.org,2005:Paper/48972024-02-14T14:57:13Z2024-02-19T16:23:56ZPyTASER: Simulating transient absorption spectroscopy (TAS) for crystals from first principlesacceptedv2.2.02023-10-24 15:23:57 UTC942024-02-14 14:57:13 UTC920245999SavyasanchiAggarwalThomas Young Centre and Department of Materials, Imperial College London, London, United Kingdom, Thomas Young Centre and Department of Chemistry, University College London, London, United Kingdom0009-0007-7128-3465SeánR.KavanaghThomas Young Centre and Department of Materials, Imperial College London, London, United Kingdom, Thomas Young Centre and Department of Chemistry, University College London, London, United Kingdom0000-0003-4577-9647YoungWonWooThomas Young Centre and Department of Materials, Imperial College London, London, United Kingdom, Department of Materials Science and Engineering, Yonsei University, Seoul, KoreaLucasG.VergaThomas Young Centre and Department of Materials, Imperial College London, London, United Kingdom0000-0002-7453-238XAlexM.GanoseDepartment of Chemistry, Imperial College London, London, United Kingdom0000-0002-4486-3321AronWalshThomas Young Centre and Department of Materials, Imperial College London, London, United Kingdom0000-0001-5460-703310.21105/joss.05999https://doi.org/10.5281/zenodo.10634762Pythonhttps://joss.theoj.org/papers/10.21105/joss.05999.pdfmaterials science, first-principles, optics, differential-absorption, spectroscopy, density functional theorytag:joss.theoj.org,2005:Paper/46212023-11-03T12:44:49Z2023-11-04T00:00:43ZModeCouplingTheory.jl: A solver for mode-coupling-theory-like integro-differential equationsaccepted0.8.02023-07-24 09:19:10 UTC912023-11-03 12:44:49 UTC820235737IlianPihlajamaaSoft Matter and Biological Physics, Department of Applied Physics, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, Netherlands0000-0003-3779-4281CorentinC.l.LaudicinaSoft Matter and Biological Physics, Department of Applied Physics, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, Netherlands0009-0000-1888-2417ThomasVoigtmannInstitut für Materialphysik im Weltraum, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Köln, 51170, Germany, Heinrich Heine University, Universitätsstraße 1, Düsseldorf, 40225, Germany0000-0002-1261-9295LiesbethM.c.JanssenSoft Matter and Biological Physics, Department of Applied Physics, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, Netherlands0000-0001-5283-133010.21105/joss.05737https://doi.org/10.5281/zenodo.10036791Juliahttps://joss.theoj.org/papers/10.21105/joss.05737.pdfjulia, python, dynamics, glasses, liquids, integral equations, differential equationstag:joss.theoj.org,2005:Paper/36992023-10-18T00:52:56Z2023-10-19T00:00:30ZDPFEHM: a differentiable subsurface physics simulatoracceptedv0.1.02022-07-01 18:45:46 UTC902023-10-18 00:52:56 UTC820234560DanielO'MalleyLos Alamos National Laboratory, USA0000-0003-0432-3088SarahY.GreerLos Alamos National Laboratory, USA, Massachussets Institute of Technology, USA0000-0001-6463-0296AleksandraPachalievaLos Alamos National Laboratory, USA0000-0003-1246-0410WuHaoLos Alamos National Laboratory, USA0000-0002-9402-7401DylanHarpThe Freshwater Trust, USA0000-0001-9777-8000VelimirV.VesselinovSmartTensors, LLC, USA0000-0002-6222-053010.21105/joss.04560https://doi.org/10.5281/zenodo.8329952Juliahttps://joss.theoj.org/papers/10.21105/joss.04560.pdfhydrology, multiphase flow, transport, wave equationtag:joss.theoj.org,2005:Paper/46082023-09-28T19:37:54Z2023-09-29T11:54:28ZBlackBIRDS: Black-Box Inference foR Differentiable Simulatorsacceptedv1.02023-07-17 13:26:44 UTC892023-09-28 19:37:54 UTC820235776ArnauQuera-BofarullDepartment of Computer Science, University of Oxford, UK, Institute for New Economic Thinking, University of Oxford, UK0000-0001-5055-9863JoelDyerDepartment of Computer Science, University of Oxford, UK, Institute for New Economic Thinking, University of Oxford, UK0000-0002-8304-8450AnisoaraCalinescuDepartment of Computer Science, University of Oxford, UK0000-0003-2082-734XJ.DoyneFarmerInstitute for New Economic Thinking, University of Oxford, UK, Mathematical Institute, University of Oxford, UK, Santa Fe Institute, USA0000-0001-7871-073XMichaelWooldridgeDepartment of Computer Science, University of Oxford, UK0000-0002-9329-841010.21105/joss.05776https://doi.org/10.5281/zenodo.8377044Pythonhttps://joss.theoj.org/papers/10.21105/joss.05776.pdfBayesian inference, differentiable simulators, variational inference, Markov chain Monte Carlotag:joss.theoj.org,2005:Paper/44462023-09-06T21:43:32Z2023-09-07T13:47:17Zxinvert: A Python package for inversion problems in geophysical fluid dynamicsacceptedv0.1.02023-04-21 22:00:51 UTC892023-09-06 21:43:32 UTC820235510Yu-KunQianState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China0000-0001-5660-761910.21105/joss.05510https://doi.org/10.5281/zenodo.8320324Pythonhttps://joss.theoj.org/papers/10.21105/joss.05510.pdfgeophysics, atmosphere, ocean, geophysical fluid dynamics, steady state problem, second-order partial differential equation, successive over relaxationtag:joss.theoj.org,2005:Paper/41612023-07-22T03:05:19Z2023-07-23T00:01:35ZBridgeStan: Efficient in-memory access to the methods of a Stan modelacceptedv.1.0.02023-01-10 21:55:16 UTC872023-07-22 03:05:19 UTC820235236EdwardA.RoualdesCalifornia State University, Chico0000-0002-8757-3463BrianWardCenter for Computational Mathematics, Flatiron Institute0000-0002-9841-3342BobCarpenterCenter for Computational Mathematics, Flatiron Institute0000-0002-2433-9688AdrianSeyboldtPyMC Labs0000-0002-4239-4541SethD.AxenCluster of Excellence Machine Learning: New Perspectives for Science, University of Tübingen0000-0003-3933-824710.21105/joss.05236https://doi.org/10.5281/zenodo.8169248R, C, Juliahttps://joss.theoj.org/papers/10.21105/joss.05236.pdfStan, Python, Rust, C++, automatic differentiationtag:joss.theoj.org,2005:Paper/43582023-07-19T17:41:02Z2023-07-20T00:01:41ZPhysics-Informed Neural networks for Advanced modelingaccepted0.0.22023-03-21 14:04:01 UTC872023-07-19 17:41:02 UTC820235352DarioCosciaSISSA, International School of Advanced Studies, Via Bonomea 265, Trieste, Italy0000-0001-8833-6833AnnaIvagnesSISSA, International School of Advanced Studies, Via Bonomea 265, Trieste, Italy0000-0002-2369-4493NicolaDemoSISSA, International School of Advanced Studies, Via Bonomea 265, Trieste, Italy0000-0003-3107-9738GianluigiRozzaSISSA, International School of Advanced Studies, Via Bonomea 265, Trieste, Italy0000-0002-0810-881210.21105/joss.05352https://doi.org/10.5281/zenodo.8163732Pythonhttps://joss.theoj.org/papers/10.21105/joss.05352.pdfpython, deep learning, physics-informed neural networks, scientific machine learning, differential equations.