tag:joss.theoj.org,2005:/papers/tagged/performance%20modelingJournal of Open Source Software2024-03-09T08:42:01ZJournal of Open Source Softwarehttps://joss.theoj.orgtag: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/39792023-03-21T11:34:30Z2023-03-22T00:03:16ZHigh-performance neural population dynamics modeling enabled by scalable computational infrastructureacceptedv1.0.02022-10-26 06:03:04 UTC832023-03-21 11:34:30 UTC820235023AashishN.PatelDepartment of Electrical and Computer Engineering, University of California San Diego, United States of America, Institute for Neural Computation, University of California San Diego, United States of AmericaAndrewR.SedlerCenter for Machine Learning, Georgia Institute of Technology, United States of America, Department of Biomedical Engineering, Georgia Institute of Technology, United States of America0000-0001-9480-0698JingyaHuangDepartment of Electrical and Computer Engineering, University of California San Diego, United States of AmericaChethanPandarinathCenter for Machine Learning, Georgia Institute of Technology, United States of America, Department of Biomedical Engineering, Georgia Institute of Technology, United States of America, Department of Neurosurgery, Emory University, United States of America, These authors contributed equallyVikashGiljaDepartment of Electrical and Computer Engineering, University of California San Diego, United States of America, These authors contributed equally10.21105/joss.05023https://doi.org/10.5281/zenodo.7719505Python, Smartyhttps://joss.theoj.org/papers/10.21105/joss.05023.pdfautolfads, kubeflow, ray, neurosciencetag:joss.theoj.org,2005:Paper/37522022-11-25T07:39:28Z2022-11-26T00:00:44Zmetrica: an R package to evaluate prediction performance of regression and classification point-forecast modelsacceptedv2.0.12022-07-29 23:41:36 UTC792022-11-25 07:39:28 UTC720224655AdrianA.CorrendoDepartment of Agronomy, Kansas State University, Manhattan, KS, USA.0000-0002-4172-289XLuizH. MoroRossoPrivate Consultant, Brasil.0000-0002-8642-911XCarlosH.HernandezDepartment of Agronomy, Kansas State University, Manhattan, KS, USA.0000-0001-5171-2516LeonardoM.BastosDepartment of Crop and Soil Sciences, University of Georgia, Athens, GA, USA.0000-0001-8958-6527LucianaNietoDepartment of Agronomy, Kansas State University, Manhattan, KS, USA.0000-0002-7172-0799DeanHolzworthCSIRO Agriculture and Food, Australia.IgnacioA.CiampittiDepartment of Agronomy, Kansas State University, Manhattan, KS, USA.0000-0001-9619-512910.21105/joss.04655https://doi.org/10.5281/zenodo.7291776Rhttps://joss.theoj.org/papers/10.21105/joss.04655.pdfAPSIM, Machine Learning, error metrics, prediction qualitytag:joss.theoj.org,2005:Paper/25722022-11-08T04:00:51Z2022-11-09T00:00:44ZPERFORM: A Python package for developing reduced-order models for reacting fluid flowsacceptedv0.12021-04-13 21:07:29 UTC792022-11-08 04:00:51 UTC720223428ChristopherR.WentlandDepartment of Aerospace Engineering, University of Michigan0000-0002-8500-569XKarthikDuraisamyDepartment of Aerospace Engineering, University of Michigan10.21105/joss.03428https://doi.org/10.5281/zenodo.7302346Pythonhttps://joss.theoj.org/papers/10.21105/joss.03428.pdfcombustion, reduced-order modelstag:joss.theoj.org,2005:Paper/32822022-03-22T12:33:30Z2022-03-23T00:00:45ZPyPVRPM: Photovoltaic Reliability and Performance Model in Pythonacceptedv1.6.02022-01-13 23:30:03 UTC712022-03-22 12:33:30 UTC720224093BrandonSilvaUniversity of Central FloridaPaulLunisUniversity of Central FloridaMariosTheristisSandia National LaboratoriesHubertSeigneurUniversity of Central Florida10.21105/joss.04093https://doi.org/10.5281/zenodo.6355115Pythonhttps://joss.theoj.org/papers/10.21105/joss.04093.pdfLCOE, Photovoltaic, Solar, Energy, Cost modeltag:joss.theoj.org,2005:Paper/25352021-04-21T09:33:12Z2021-04-22T00:02:22Zperformance: An R Package for Assessment, Comparison and Testing of Statistical Modelsaccepted0.7.12021-03-23 10:28:04 UTC602021-04-21 09:33:12 UTC620213139DanielLüdeckeUniversity Medical Center Hamburg-Eppendorf, Germany0000-0002-8895-3206MattanS.Ben-ShacharBen-Gurion University of the Negev, Israel0000-0002-4287-4801IndrajeetPatilCenter for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany0000-0003-1995-6531PhilipWaggonerUniversity of Chicago, USA0000-0002-7825-7573DominiqueMakowskiNanyang Technological University, Singapore0000-0001-5375-996710.21105/joss.03139https://doi.org/10.5281/zenodo.4700887Rhttps://joss.theoj.org/papers/10.21105/joss.03139.pdfeasystats, parameters, regression, linear models, coefficientstag:joss.theoj.org,2005:Paper/15832020-07-16T07:46:48Z2021-02-15T11:30:53ZldaPrototype: A method in R to get a Prototype of multiple Latent Dirichlet Allocationsacceptedv0.1.12020-03-10 15:00:29 UTC512020-07-16 07:46:48 UTC520202181JonasRiegerTU Dortmund University0000-0002-0007-447810.21105/joss.02181https://doi.org/10.5281/zenodo.3945836Rhttps://joss.theoj.org/papers/10.21105/joss.02181.pdftopic modeling, natural language processing, text data, tuning, model selection, high performance computing, parallelizationtag:joss.theoj.org,2005:Paper/7052019-06-12T16:15:44Z2021-02-19T14:34:34ZReinforcementLearning: A Package to Perform Model-Free Reinforcement Learning in Racceptedv1.0.22018-10-22 17:31:07 UTC382019-06-12 16:15:44 UTC420191087NicolasPröellochsUniversity of Giessen, University of OxfordStefanFeuerriegelETH Zurich10.21105/joss.01087https://doi.org/10.5281/zenodo.3244170Rhttps://joss.theoj.org/papers/10.21105/joss.01087.pdfReinforcement Learning, Batch Learning, Experience Replay, Q-Learningtag:joss.theoj.org,2005:Paper/3582018-06-26T13:41:50Z2021-02-15T11:33:41ZLimbo: A Flexible High-performance Library for Gaussian Processes modeling and Data-Efficient OptimizationacceptedV2.02018-01-22 15:06:54 UTC262018-06-26 13:41:50 UTC32018545AntoineCullyPersonal Robotics Lab, Imperial College London, London, United Kingdom0000-0002-3190-7073KonstantinosChatzilygeroudisInria, CNRS, Université de Lorraine, LORIA, Nancy, France0000-0003-3585-1027FedericoAllocatiInria, CNRS, Université de Lorraine, LORIA, Nancy, FranceJean-BaptisteMouretInria, CNRS, Université de Lorraine, LORIA, Nancy, France0000-0002-2513-027X10.21105/joss.00545https://doi.org/10.5281/zenodo.1298561C++, Pythonhttps://joss.theoj.org/papers/10.21105/joss.00545.pdfGaussian Processes, Bayesian Optimization, C++11tag:joss.theoj.org,2005:Paper/72016-05-11T00:00:00Z2021-02-15T11:34:35ZApplication Skeleton: Generating Synthetic Applications for Infrastructure Researchacceptedv1.22016-05-11 15:38:44 UTC12016-05-11 00:00:00 UTC1201617ZhaoZhangAMPLab and BIDS, University of California, Berkeley0000-0001-5921-0035DanielS.KatzNational Center for Supercomputing Applications, University of Illinois Urbana-Champaign0000-0001-5934-7525AndreMerzkyRADICAL Laboratory, Rutgers University0000-0002-7228-4327MatteoTurilliRADICAL Laboratory, Rutgers University0000-0003-0527-1435ShantenuJhaRADICAL Laboratory, Rutgers University0000-0002-5040-026XYaduNandComputation Institute, University of Chicago0000-0002-9162-600310.21105/joss.00017https://doi.org/10.5281/zenodo.13750Python, Chttps://joss.theoj.org/papers/10.21105/joss.00017.pdfcomputational science, data science, application modeling, system modeling, performance modeling, parallel and distributed systems