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href ="#about "> About</ a >
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+ href ="#showcase "> Spotlight </ a >
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href ="#publications "> Publications</ a >
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+ < div class ="card h-100 ">
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+ < img class ="card-img-top " src ="./assets/img/logos/never2_480_270.png " alt ="NeVer 2 ">
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+ < div class ="card-body ">
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+ < h4 class ="card-title ">
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+ < a target ="_blank " href ="https://github.com/NeVerTools/NeVer2 "> NeVer 2</ a >
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+ </ h4 >
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+ < p class ="card-text ">
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+ < span class ="badge badge-primary "> Tool</ span >
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+ < span class ="badge badge-info "> 2.0.1</ span >
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+ </ br > </ br > A tool for learning and verification of neural networks.</ br >
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+ <!--
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+ <h6 class="card-title" style="color: #1abc9c">Examples</h6>
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+ <a target="_blank" href="tutorial_james.html">Feed-Forward NN</a>
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+ </span>
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+ <span class="badge badge-light">
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+ <a target="_blank" href="tutorial_fmnist.html">Convolutional NN</a>
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+ </span>
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+ -->
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+ </ p >
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+ </ div >
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+ </ div >
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+ </ div >
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< span class ="badge badge-primary "> API</ span >
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- < span class ="badge badge-info "> 1.0.0 </ span >
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</ br > </ br > A Python library for learning and verification of neural networks and other machine learning models.
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- < a target ="_blank " href ="https://github.com/NeVerTools/NeVer2 "> NeVer 2</ a >
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- < span class ="badge badge-primary "> Tool</ span >
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- < span class ="badge badge-info "> Beta</ span >
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- </ br > </ br > A tool for learning and verification of neural networks.</ br >
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- < h6 class ="card-title " style ="color: #1abc9c "> Examples</ h6 >
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- < span class ="badge badge-light ">
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- < a target ="_blank " href ="tutorial_james.html "> Feed-Forward NN</ a >
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- </ span >
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- < a target ="_blank " href ="tutorial_fmnist.html "> Convolutional NN</ a >
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< img class ="card-img-top " src ="./assets/img/logos/VNNLIB_480_270.png " alt ="VNN-LIB ">
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< a target ="_blank " href ="http://www.vnnlib.org/ "> VNN-LIB</ a >
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- < span class ="badge badge-primary "> Initiative </ span >
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+ < span class ="badge badge-primary "> Standard </ span >
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</ br > </ br > An international initiative whose aim is to encourage collaboration and facilitate research and development in Verification of Neural Networks (VNN).
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<!-- About Section Content-->
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- < p class ="pre-wrap lead "> This is the home page of neuralverification.org, an initiative of researchers working at the < a href ="https://www.dibris.unige.it " style ="color:#343a40 "> Department of Informatics, Bioengineering, Robotics and Systems Engineering</ a > of the < a href ="https://www.unige.it " style ="color:#343a40 "> University of Genoa.</ a > </ p >
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- < p class ="pre-wrap lead "> The aim of the initiative is to develop tools that can verify neural networks and other machine learned programs as well as standard, i.e., manually written, code.</ p >
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+ < p class ="pre-wrap lead "> This is the home page of neuralverification.org, an initiative of researchers from
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+ < a href ="https://www.unige.it " style ="color:#343a40 "> University of Genoa</ a > , < a href ="https://www.uniss.it " style ="color:#343a40 "> University of Sassari</ a > and < a href ="https://www.kent.ac.uk/ " style ="color:#343a40 "> University of Kent</ a > .</ p >
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+ < p class ="pre-wrap lead "> The aim of the initiative is to develop tools to verify neural networks and other machine learned programs
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+ as well as standard, i.e., manually written, code.</ p >
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- < h2 class ="page-section-heading text-secondary d-inline-block mb-0 "> Showcase </ h2 >
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<!-- Copyright Section -->
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< section class ="copyright py-4 text-center text-white ">
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- < div class ="container "> < small class ="pre-wrap "> < a target ="_blank " href ="https://github.com/NeVerTools/NeVerTools.github.io/blob/master/LICENSE "> MIT Licensed</ a > | neuralverification.org 2024 | Hosted with ❤ by < a href ="https://github.com/ " target ="_blank "> GitHub</ a > </ small > </ div >
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+ < div class ="container "> < small class ="pre-wrap "> < a target ="_blank " href ="https://github.com/NeVerTools/NeVerTools.github.io/blob/master/LICENSE "> MIT Licensed</ a > | neuralverification.org 2025 | Hosted with ❤ by < a href ="https://github.com/ " target ="_blank "> GitHub</ a > </ small > </ div >
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