tag:joss.theoj.org,2005:/papers/tagged/learningJournal of Open Source Software2024-03-27T23:48:03ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/51402024-03-27T23:48:03Z2024-03-28T15:06:00ZTDApplied: An R package for machine learning and inference with persistence diagramsacceptedv3.0.22024-01-25 19:46:31 UTC952024-03-27 23:48:03 UTC920246321ShaelBrownDepartment of Quantitative Life Sciences, McGill University, Montreal, Canada0000-0001-8868-2867RezaFarivar-MohseniMcGill Vision Research, Department of Opthamology, McGill University, Montreal, Canada0000-0002-3123-262710.21105/joss.06321https://doi.org/10.5281/zenodo.10814141R, C++, Chttps://joss.theoj.org/papers/10.21105/joss.06321.pdftopological data analysis, persistent homologytag:joss.theoj.org,2005:Paper/48242024-03-18T12:36:12Z2024-03-19T00:01:19ZShapelets: A Python package implementing shapelet functions and their applicationsacceptedv0.12023-09-30 00:32:46 UTC952024-03-18 12:36:12 UTC920246058MatthewPeresTinoDepartment of Chemical Engineering, University of Waterloo, Ontario, Canada0009-0005-6832-1761AbbasYusufAbdulazizDepartment of Chemical Engineering, University of Waterloo, Ontario, CanadaRobertSudermanGoogle Inc.ThomasAkdenizEast Coast Asset Management SEZCNasserMohieddinAbukhdeirDepartment of Chemical Engineering, University of Waterloo, Ontario, Canada, Department of Physics and Astronomy, University of Waterloo, Ontario, Canada, Waterloo Institute for Nanotechnology, University of Waterloo, Ontario, Canada0000-0002-1772-037610.21105/joss.06058https://doi.org/10.5281/zenodo.10819578Pythonhttps://joss.theoj.org/papers/10.21105/joss.06058.pdfshapelets, self-assembly, astronomy, image processing, machine learningtag:joss.theoj.org,2005:Paper/48542024-03-18T12:28:23Z2024-03-19T00:01:17ZImbalance: A comprehensive multi-interface Julia toolbox to address class imbalanceacceptedv0.1.22023-10-17 14:48:00 UTC952024-03-18 12:28:23 UTC920246310EssamWisamCairo University, Egypt0009-0009-1198-7166AnthonyBlaomUniversity of Auckland, New Zealand0000-0001-6689-886X10.21105/joss.06310https://doi.org/10.5281/zenodo.10823254Juliahttps://joss.theoj.org/papers/10.21105/joss.06310.pdfmachine learning, classification, class imbalance, resampling, oversampling, undersampling, juliatag:joss.theoj.org,2005:Paper/50042024-03-17T15:00:35Z2024-03-18T07:46:38ZSelfEEG: A Python library for Self-Supervised Learning in Electroencephalographyacceptedv0.1.02023-12-16 00:30:46 UTC952024-03-17 15:00:35 UTC920246224FedericoDel PupDepartment of Information Engineering, University of Padova, Padova, Italy, Department of Neuroscience, University of Padova, Padova, Italy, Padova Neuroscience Center, University of Padova, Padova, Italy0009-0004-0698-962XAndreaZanolaPadova Neuroscience Center, University of Padova, Padova, Italy0000-0001-6973-8634Louis FabriceTshimangaDepartment of Neuroscience, University of Padova, Padova, Italy, Padova Neuroscience Center, University of Padova, Padova, Italy0009-0002-1240-4830Paolo EmilioMazzonPadova Neuroscience Center, University of Padova, Padova, ItalyManfredoAtzoriDepartment of Neuroscience, University of Padova, Padova, Italy, Padova Neuroscience Center, University of Padova, Padova, Italy, Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO Valais), Sierre, Switzerland0000-0001-5397-206310.21105/joss.06224https://doi.org/10.5281/zenodo.10813095Jupyter Notebook, Pythonhttps://joss.theoj.org/papers/10.21105/joss.06224.pdfPyTorch, Deep Learning (DL), Self-Supervised Learning (SSL), Contrastive Learning (CL), Electroencephalography (EEG), Biomedical signalstag:joss.theoj.org,2005:Paper/44492024-03-14T19:57:22Z2024-03-15T00:01:22ZOmniTrax: A deep learning-driven multi-animal tracking and pose-estimation add-on for Blenderacceptedv0.2.22023-04-23 08:59:26 UTC952024-03-14 19:57:22 UTC920245549FabianPlumImperial College London, Department of Bioengineering, United Kingdom0000-0003-1012-664610.21105/joss.05549https://doi.org/10.5281/zenodo.10817891Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05549.pdfBlender, multi-object tracking, pose-estimation, deep learningtag:joss.theoj.org,2005:Paper/46832024-03-09T08:42:01Z2024-03-10T00:01:18ZPerMetrics: A Framework of Performance Metrics for Machine Learning Modelsacceptedv1.4.22023-08-08 05:27:41 UTC952024-03-09 08:42:01 UTC920246143NguyenVan ThieuFaculty of Computer Science, Phenikaa University, Yen Nghia, Ha Dong, Hanoi, 12116, Vietnam.0000-0001-9994-874710.21105/joss.06143https://doi.org/10.5281/zenodo.3951205Pythonhttps://joss.theoj.org/papers/10.21105/joss.06143.pdfmodel assessment tools, performance metrics, classification validation metrics, regression evaluation criteria, clustering criterion indices, machine learning metricstag:joss.theoj.org,2005:Paper/44372024-03-08T22:12:15Z2024-03-10T08:11:09ZEthome: tools for machine learning of animal behavioracceptedv0.6.02023-04-18 06:25:31 UTC952024-03-08 22:12:15 UTC920245623BenjaminLansdellDevelopmental Neurobiology, St Jude Children's Research Hospital, Memphis, Tennessee, United States of America0000-0003-1444-1950AbbasShirinifardDevelopmental Neurobiology, St Jude Children's Research Hospital, Memphis, Tennessee, United States of America10.21105/joss.05623https://doi.org/10.5281/zenodo.10680136Python, Rubyhttps://joss.theoj.org/papers/10.21105/joss.05623.pdfsupervised-learning, deeplabcut, boris, neurodata-without-borders, pose-tracking, ndx-pose, animal-behaviortag:joss.theoj.org,2005:Paper/48582024-03-06T17:32:25Z2024-03-07T00:00:24Zcalorine: A Python package for constructing and sampling neuroevolution potential modelsacceptedv2.02023-10-21 15:02:27 UTC952024-03-06 17:32:25 UTC920246264EricLindgrenDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-8549-6839MagnusRahmDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-6777-0371ErikFranssonDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0001-5262-3339FredrikErikssonDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-7945-5483NicklasÖsterbackaDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-6043-4607ZheyongFanCollege of Physical Science and Technology, Bohai University, Jinzhou 121013, P. R. China0000-0002-2253-8210PaulErhartDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-2516-606110.21105/joss.06264https://doi.org/10.5281/zenodo.10723374Python, C++, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.06264.pdfcondensed matter, machine learning, interatomic potentials, force fields, molecular dynamics, neuroevolution, neural networktag:joss.theoj.org,2005:Paper/47452024-03-03T08:56:11Z2024-03-09T08:34:29ZDICaugment: A Python Package for 3D Medical Imaging Augmentationacceptedv1.0.02023-09-10 23:37:02 UTC952024-03-03 08:56:11 UTC920246120J.McIntoshDivision of Imaging, Diagnostics, and Software Reliability, CDRH, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA0009-0008-2573-180XQianCaoDivision of Imaging, Diagnostics, and Software Reliability, CDRH, U.S. Food and Drug Administration, Silver Spring, MD 20993, USABerkmanSahinerDivision of Imaging, Diagnostics, and Software Reliability, CDRH, U.S. Food and Drug Administration, Silver Spring, MD 20993, USANicholasPetrickDivision of Imaging, Diagnostics, and Software Reliability, CDRH, U.S. Food and Drug Administration, Silver Spring, MD 20993, USAM.MehdiFarhangiDivision of Imaging, Diagnostics, and Software Reliability, CDRH, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA10.21105/joss.06120https://doi.org/10.5281/zenodo.10738855Pythonhttps://joss.theoj.org/papers/10.21105/joss.06120.pdfAugmentation, Deep Learning, Medical, tag: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, Preconditioners