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<!DOCTYPE html>
<html lang="en">
<head>
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content="NeVer Tools collects knowledge and insight about formal verification of Neural Networks.">
<meta name="author" content="Navendu Pottekkat | Stefano Demarchi">
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<h1 class="masthead-heading mb-0">Neural Verification</h1>
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<p class="pre-wrap masthead-subheading font-weight-light mb-0">Automated verification of neural networks,
machine learned and standard programs.</p>
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<img class="card-img-top" src="./assets/img/logos/never2_480_270.png" alt="NeVer 2">
<div class="card-body">
<h4 class="card-title">
<a target="_blank" href="https://github.com/NeVerTools/NeVer2">NeVer 2</a>
</h4>
<p class="card-text">
<span class="badge badge-primary">Tool</span>
<span class="badge badge-info">2.0.2</span>
</br></br>A tool for learning and verification of neural networks.</br>
<!-- <h6 class="card-title" style="color: #1abc9c">Examples</h6>
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<img class="card-img-top" src="./assets/img/logos/nevertools_480_270.png" alt="pyNeVer">
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<a target="_blank" href="https://github.com/NeVerTools/pyNeVer">pyNeVer</a>
</h4>
<p class="card-text">
<span class="badge badge-primary">API</span>
<span class="badge badge-info">1.2.5</span>
<span class="badge badge-light">
<a target="_blank" href="pynever/index.html">Documentation</a>
</span>
</br></br>A Python library for learning and verification of neural networks and other
machine learning models.
</p>
</div>
</div>
</div>
<!-- <div class="col-lg-4 col-sm-6 mb-4">
<div class="card h-100">
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<a target="_blank" href="https://github.com/NeVerTools/CoCoNet">CoCoNet</a>
</h4>
<p class="card-text">
<span class="badge badge-primary">Tool</span>
<span class="badge badge-info">Alpha</span>
</br></br>A tool for construction and conversion of neural networks across different standards.
<h6 class="card-title" style="color: #1abc9c">Examples</h6>
<span class="badge badge-light">
<a target="_blank" href="coconet_guide.html">User Guide</a>
</span>
</p>
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</div> -->
<div class="col-lg-4 col-sm-6 mb-4">
<div class="card h-100">
<img class="card-img-top" src="./assets/img/logos/VNNLIB_480_270.png" alt="VNN-LIB">
<div class="card-body">
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<a target="_blank" href="http://www.vnnlib.org/">VNN-LIB</a>
</h4>
<p class="card-text">
<span class="badge badge-primary">Standard</span>
</br></br>An international initiative whose aim is to encourage collaboration and
facilitate research and development in Verification of Neural Networks (VNN).
</p>
</div>
</div>
</div>
<div class="col-lg-4 col-sm-6 mb-4">
<div class="card h-100">
<img class="card-img-top" src="./assets/img/logos/Scan_480_270.png" alt="sCan">
<div class="card-body">
<h4 class="card-title">
<a target="_blank" href="https://github.com/convince-project/scan">SCAn</a>
</h4>
<p class="card-text">
<span class="badge badge-primary">Tool</span>
<span class="badge badge-warning">CONVINCE EU project</span>
</br></br>A statistical code analyzer developed for the EU project <a target="_blank"
href="https://convince-project.eu/">CONVINCE</a>.
</p>
</div>
</div>
</div>
<div class="col-lg-4 col-sm-6 mb-4">
<div class="card h-100">
<img class="card-img-top" src="./assets/img/logos/moco_logo_480_270.png" alt="MOCO">
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<a target="_blank" href="https://github.com/neverTools/moco">MOCO</a>
</h4>
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<span class="badge badge-primary">Tool</span>
<span class="badge badge-light">
<a target="_blank" href="https://nevertools.github.io/MOCO/index.html">Documentation</a>
</span>
</br></br> A Tool to convert files in RoaML data model into plain SCXML files
</p>
</div>
</div>
</div>
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</div>
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<!-- ABOUT SECTION -->
<section class="page-section bg-primary text-white mb-0" id="about">
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<div class="text-center">
<p class="pre-wrap lead">This is the home page of neuralverification.org, an initiative of researchers
from
<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>
<p class="pre-wrap lead">The aim of the initiative is to develop tools to verify neural networks and
other machine learned programs
as well as standard, i.e., manually written, code.</p>
</div>
</div>
</section>
<!-- SHOWCASE SECTION -->
<section class="page-section" id="showcase">
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</br></br>
<a href="assets/doc/never2.pdf" class="divider-custom-icon" download="NeVer2 paper"><button
class="btn"><i class="fa fa-download"></i> Download paper</button></a>
</div>
</div>
</div>
</section>
<!-- PUBLICATIONS SECTION -->
<section class="page-section bg-primary text-white mb-0" id="publications">
<div class="container">
<!-- Publications Section Heading-->
<div class="text-center">
<h2 class="page-section-heading d-inline-block text-white">Publications</h2>
</div>
<!-- Icon Divider-->
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<!-- About Section Content-->
<div class="text-left">
<ul>
<!-- 2024 -->
<li>
<h4 class="treeview">2024</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">S. Demarchi, D. Guidotti, L. Pulina and A. Tacchella</p>
<h5>NeVer2: Learning and Verification of Neural Networks <span
class="badge badge-warning">Article</span></h5>
<p class="pre-wrap authors">Soft Computing</p>
</li>
<li>
<p class="pre-wrap lead">S. Demarchi, A. Gimelli and A. Tacchella</p>
<h5>Improving Abstract Propagation for Verification of Neural Networks <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">International ECMS Conference on Modeling and Simulation</p>
</li>
</ul>
</li>
<!-- 2023 -->
<li>
<h4 class="treeview">2023</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">S. Demarchi, D. Guidotti, L. Pulina and A. Tacchella</p>
<h5>Supporting Standardization of Neural Networks Verification with VNN-LIB and CoCoNet
<span class="badge badge-secondary">Conference</span>
</h5>
<p class="pre-wrap authors">FoMLAS Workshop, Computer-Aided Verification</p>
</li>
<li>
<p class="pre-wrap lead">S. Demarchi</p>
<h5>Experimenting with Constraint Programming Techniques in Artificial Intelligence:
Automated System Design and Verification of Neural Networks <span
class="badge badge-success">Thesis</span></h5>
<p class="pre-wrap authors">PhD Thesis</p>
</li>
<li>
<p class="pre-wrap lead">D. Guidotti, S. Demarchi, L. Pulina and A. Tacchella</p>
<h5>Evaluating Reachability Algorithms for Neural Networks on NeVer2 <span
class="badge badge-light">Preprint</span></h5>
<p class="pre-wrap authors">Submitted for peer review</p>
</li>
</ul>
</li>
<!-- 2022 -->
<li>
<h4 class="treeview">2022</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">D. Guidotti</p>
<h5>Verification and Repair of Machine Learning Models <span
class="badge badge-success">Thesis</span></h5>
<p class="pre-wrap authors">PhD Thesis</p>
</li>
<li>
<p class="pre-wrap lead">S. Demarchi and D. Guidotti</p>
<h5>Counter-Example Guided Abstract Refinement for Verification of Neural Networks <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">CPS Summer School Workshop, PhD workshop</p>
</li>
<li>
<p class="pre-wrap lead">S. Demarchi, D. Guidotti, A. Pitto and A. Tacchella</p>
<h5>Formal Verification of Neural Networks: a Case Study about Adaptive Cruise Control
<span class="badge badge-secondary">Conference</span>
</h5>
<p class="pre-wrap authors">International ECMS Conference on Modeling and Simulation</p>
</li>
</ul>
</li>
<!-- 2021 -->
<li>
<h4 class="treeview">2021</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">D. Guidotti</p>
<h5>Verification and Repair of Neural Networks <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">AAAI Conference on Artificial Intelligence</p>
</li>
<li>
<p class="pre-wrap lead">D. Guidotti, L. Pulina and A. Tacchella</p>
<h5>pyNeVer: a Framework for Learning and Verification of Neural Networks <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">Automated Technology for Verification and Analysis</p>
</li>
<li>
<p class="pre-wrap lead">D. Guidotti, G. Cicala, T. Gili and A. Tacchella</p>
<h5>Telling Faults From Cyber-Attacks In A Multi-Modal Logistic System With Complex
Network Analysis <span class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">International ECMS Conference on Modeling and Simulation</p>
</li>
<li>
<p class="pre-wrap lead">D. Guidotti</p>
<h5>Safety Analysis of Deep Neural Networks <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">International Joint Conference on Artificial Intelligence
(IJCAI)</p>
</li>
</ul>
</li>
<!-- 2020 -->
<li>
<h4 class="treeview">2020</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">D. Guidotti, F. Leofante, L. Pulina and A. Tacchella</p>
<h5>Verification of Neural Networks: Enhancing Scalability through Pruning <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">European Conference on Artificial Intelligence</p>
</li>
</ul>
</li>
<!-- 2012 -->
<li>
<h4 class="treeview">2012</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">L. Pulina and A. Tacchella</p>
<h5>Challenging SMT solvers to verifiy Neural Networks <span
class="badge badge-warning">Article</span></h5>
<p class="pre-wrap authors">AI Communications</p>
</li>
</ul>
</li>
<!-- 2011 -->
<li>
<h4 class="treeview">2011</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">L. Pulina and A. Tacchella</p>
<h5>NeVer: a Tool for Artificial Neural Networks Verification <span
class="badge badge-warning">Article</span></h5>
<p class="pre-wrap authors">Annals of Mathematics and Artificial Intelligence</p>
</li>
<li>
<p class="pre-wrap lead">L. Pulina and A. Tacchella</p>
<h5>Checking Safety of Neural Networks with SMT Solvers: A Comparative Evaluation <span
class="badge badge-secondary">Conference</span></h5>
<p class="pre-wrap authors">International Conference of AI*IA</p>
</li>
</ul>
</li>
<!-- 2010 -->
<li>
<h4 class="treeview">2010</h4>
<ul class="tw-nested">
<li>
<p class="pre-wrap lead">L. Pulina and A. Tacchella</p>
<h5>An Abstraction-Refinement Approach to Verification of Artificial Neural Networks
<span class="badge badge-secondary">Conference</span>
</h5>
<p class="pre-wrap authors">Computer Aided Verification, 22nd International Conference
</p>
</li>
</ul>
</li>
</ul>
</div>
</div>
</section>
<!-- TEAM SECTION -->
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</div>
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