tag:joss.theoj.org,2005:/papers/tagged/PyTorchJournal of Open Source Software2024-03-17T15:00:35ZJournal of Open Source Softwarehttps://joss.theoj.orgtag: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/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/48132024-02-27T21:24:38Z2024-03-22T14:09:24ZDeepRank2: Mining 3D Protein Structures with Geometric Deep Learningacceptedv2.1.02023-09-22 15:36:51 UTC942024-02-27 21:24:38 UTC920245983GiuliaCrocioniNetherlands eScience Center, Amsterdam, The Netherlands0000-0002-0823-0121DaniL.BodorNetherlands eScience Center, Amsterdam, The Netherlands0000-0003-2109-2349CoosBaakmanThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0003-4317-1566FarzanehM.PariziThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0003-4230-7492Daniel-T.RademakerThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0003-1959-1317GayatriRamakrishnanThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0001-8203-2783SvenA.van der BurgNetherlands eScience Center, Amsterdam, The Netherlands0000-0003-1250-6968DarioF.MarzellaThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0002-0043-3055JoãoM.c.TeixeiraIndependent Researcher0000-0002-9113-0622LiC.XueThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0002-2613-538X10.21105/joss.05983https://doi.org/10.5281/zenodo.10566809Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05983.pdfPyTorch, structural biology, geometric deep learning, 3D protein structures, protein-protein interfaces, single-residue variants, graph neural networks, convolutional neural networks, DeepRanktag:joss.theoj.org,2005:Paper/44572023-11-21T16:27:28Z2023-11-22T08:46:01ZQMCTorch: a PyTorch Implementation of Real-Space Quantum Monte Carlo Simulations of Molecular Systemsacceptedv0.3.02023-04-28 08:45:41 UTC912023-11-21 16:27:28 UTC820235472NicolasRenaudNetherlands eScience Center, Science Park 402, 1098 XH Amsterdam, The Netherlands0000-0001-9589-269410.21105/joss.05472https://doi.org/10.5281/zenodo.10122190Pythonhttps://joss.theoj.org/papers/10.21105/joss.05472.pdfDeep Learning, Quantum Chemistry, Monte Carlo, Molecular Systemstag:joss.theoj.org,2005:Paper/47242023-10-30T14:04:21Z2023-10-31T00:00:33ZJetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physicsacceptedv0.2.32023-08-29 16:02:38 UTC902023-10-30 14:04:21 UTC820235789RaghavKansalUC San Diego, USA, Fermilab, USA0000-0003-2445-1060CarlosParejaUC San Diego, USA0000-0002-9022-2349ZichunHaoCalifornia Institute of Technology, USA0000-0002-5624-4907JavierDuarteUC San Diego, USA0000-0002-5076-709610.21105/joss.05789https://doi.org/10.5281/zenodo.10044601Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05789.pdfPyTorch, high energy physics, machine learning, jetstag:joss.theoj.org,2005:Paper/42602023-09-20T00:32:03Z2023-09-21T00:01:17ZSpikeometric: Linear Non-Linear Cascade Spiking Neural Networks with Pytorch Geometricacceptedv1.0.02023-02-23 16:23:51 UTC892023-09-20 00:32:03 UTC820235451JakobL.SønstebøDepartment of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway0009-0009-0584-9293HermanBrunborgDepartment of Physics, University of Oslo, Oslo, NorwayMikkelElleLepperødDepartment of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway, Department of Physics, University of Oslo, Oslo, Norway0000-0002-4262-554910.21105/joss.05451https://doi.org/10.5281/zenodo.8358903Pythonhttps://joss.theoj.org/papers/10.21105/joss.05451.pdfpython, computational neuroscience, machine learning, spiking neural networks, generalized linear models, linear non-linear poisson modelstag:joss.theoj.org,2005:Paper/39652023-07-05T12:56:44Z2023-07-06T00:01:11ZDeBEIR: A Python Package for Dense Bi-Encoder Information Retrievalacceptedv0.0.12022-10-17 06:11:59 UTC872023-07-05 12:56:44 UTC820235017VincentNguyenAustralian National University, School of Computing, Commonwealth Scientific and Industrial Research Organisation, Data610000-0003-1787-8090SarvnazKarimiCommonwealth Scientific and Industrial Research Organisation, Data610000-0002-4927-3937ZhenchangXingAustralian National University, School of Computing, Commonwealth Scientific and Industrial Research Organisation, Data610000-0001-7663-142110.21105/joss.05017https://doi.org/10.5281/zenodo.8103783Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05017.pdfinformation retrieval, dense retrieval, bi-encoder, transformers, pytorch, python, deep learning, neural networks, machine learning, natural language processingtag:joss.theoj.org,2005:Paper/42212023-06-24T19:39:19Z2023-06-25T00:01:02Znormflows: A PyTorch Package for Normalizing Flowsacceptedv1.62023-02-18 13:00:57 UTC862023-06-24 19:39:19 UTC820235361VincentStimperUniversity of Cambridge, Cambridge, United Kingdom, Max Planck Institute for Intelligent Systems, Tübingen, Germany0000-0002-4965-4297DavidLiuUniversity of Cambridge, Cambridge, United KingdomAndrewCampbellUniversity of Cambridge, Cambridge, United KingdomVincentBerenzMax Planck Institute for Intelligent Systems, Tübingen, GermanyLukasRyllUniversity of Cambridge, Cambridge, United KingdomBernhardSchölkopfMax Planck Institute for Intelligent Systems, Tübingen, Germany0000-0002-8177-0925JoséMiguelHernández-LobatoUniversity of Cambridge, Cambridge, United Kingdom10.21105/joss.05361https://doi.org/10.5281/zenodo.8027667Pythonhttps://joss.theoj.org/papers/10.21105/joss.05361.pdfPyTorch, Machine Learning, Normalizing Flows, Density Estimationtag:joss.theoj.org,2005:Paper/40022023-06-24T03:50:11Z2023-06-25T00:01:08Zpytorch-widedeep: A flexible package for multimodal deep learningacceptedv1.2.12022-11-13 12:56:02 UTC862023-06-24 03:50:11 UTC820235027JavierRodriguezZaurinIndependent Researcher, Spain0000-0002-1082-1107PavolMulinkaCentre Tecnologic de Telecomunicacions de Catalunya (CTTC/CERCA), Catalunya, Spain0000-0002-9394-879410.21105/joss.05027https://doi.org/10.5281/zenodo.7908172JavaScript, Pythonhttps://joss.theoj.org/papers/10.21105/joss.05027.pdfPytorch, Deep learningtag:joss.theoj.org,2005:Paper/36842022-11-23T18:51:00Z2022-11-24T00:01:12ZFastGeodis: Fast Generalised Geodesic Distance Transformacceptedv1.0.0rc42022-06-27 21:31:17 UTC792022-11-23 18:51:00 UTC720224532MuhammadAsadSchool of Biomedical Engineering & Imaging Sciences, King’s College London, UK0000-0002-3672-2414ReubenDorentSchool of Biomedical Engineering & Imaging Sciences, King’s College London, UK0000-0002-7530-0644TomVercauterenSchool of Biomedical Engineering & Imaging Sciences, King’s College London, UK0000-0003-1794-045610.21105/joss.04532https://doi.org/10.5281/zenodo.7349069Python, C++, Cudahttps://joss.theoj.org/papers/10.21105/joss.04532.pdfPyTorch, Deep Learning, Medical Imaging, Distance Transform