tag:joss.theoj.org,2005:/papers/tagged/deep-neural-networks?page=2Journal of Open Source Software2020-01-16T00:24:45ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/12172020-01-16T00:24:45Z2021-02-15T11:31:37ZLarq: An Open-Source Library for Training Binarized Neural Networksacceptedv0.7.12019-09-13 16:57:11 UTC452020-01-16 00:24:45 UTC520201746LukasGeigerPlumerai Research0000-0002-8697-9920PlumeraiTeamPlumerai Research10.21105/joss.01746https://doi.org/10.6084/m9.figshare.11619912.v1Pythonhttps://joss.theoj.org/papers/10.21105/joss.01746.pdfpython, tensorflow, keras, deep-learning, machine-learning, binarized-neural-networks, quantized-neural-networks, efficient-deep-learningtag:joss.theoj.org,2005:Paper/4942019-01-15T20:32:49Z2021-02-15T11:33:23ZNN-SVG: Publication-Ready Neural Network Architecture Schematicsaccepted1.0.02018-05-13 13:04:48 UTC332019-01-15 20:32:49 UTC42019747AlexanderLeNailMassachusetts Institute of Technology, dept of Biological Engineering0000-0001-8173-231510.21105/joss.00747https://doi.org/10.5281/zenodo.2541121JavaScripthttps://joss.theoj.org/papers/10.21105/joss.00747.pdfmachine learning, deep learning, neural networks, visualizationtag:joss.theoj.org,2005:Paper/6392018-11-01T12:57:46Z2021-02-15T11:32:57ZTensorFlow.jl: An Idiomatic Julia Front End for TensorFlowacceptedv0.10.12018-09-24 16:19:50 UTC312018-11-01 12:57:46 UTC320181002JonathanMalmaudMassachusetts Institute of Technology0000-0002-5352-2086LyndonWhiteThe University of Western Australia0000-0003-1386-164610.21105/joss.01002https://doi.org/10.5281/zenodo.1476107Juliahttps://joss.theoj.org/papers/10.21105/joss.01002.pdfjulialang, tensorflow, machine learning, neural networks, deep learningtag:joss.theoj.org,2005:Paper/2812017-11-07T00:00:00Z2021-02-15T11:33:54ZMatDL: A Lightweight Deep Learning Library in MATLABacceptedv0.7.02017-09-17 04:07:37 UTC192017-11-07 00:00:00 UTC22017413HaythamM.FayekRMIT University0000-0002-1840-760510.21105/joss.00413https://doi.org/10.5281/zenodo.1042860Matlab, Chttps://joss.theoj.org/papers/10.21105/joss.00413.pdfMachine Learning, Deep Learning, Neural Networks