Welcome to VNN-LIB!

An international initiative whose aim is to encourage collaboration and facilitate research and development in Verification of Neural Networks (VNN)


A standard for VNN benchmarks


ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers.


SMT-LIB is an international initiative aimed at facilitating research and development in Satisfiability Modulo Theories (SMT).


CoCoNet is a tool for construction and conversion of neural networks across different standards, written in Python and relying on the pyNeVer API.


The Verification of Neural Networks Competition (VNN-COMP) aims to bring together researchers interested in methods and tools providing guarantees about the behaviours of neural networks and systems built from them.