In this work, we present an early prototype of NeVer 2.0, a new system for automated synthesis and analysis of deep neural networks.NeVer 2.0borrows its design philosophy from NeVer, the first package that integrated learning, automated verification and repair of (shallow) neural networks in a single tool. The goal of NeVer 2.0 is to provide a similar integration for deep networks by leveraging a selection of state-of-the-art learning frameworks and integrating them with verification algorithms to ease the scalability challenge and make repair of faulty networks possible.

中文翻译：

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NeVer 2.0：深度神经网络的学习、验证和修复

在这项工作中，我们展示了 NeVer 2.0 的早期原型，这是一个用于自动合成和分析深度神经网络的新系统。 NeVer 2.0 借鉴了 NeVer 的设计理念，这是第一个集成学习、自动验证和修复（浅）的包单个工具中的神经网络。NeVer 2.0 的目标是通过利用一系列最先进的学习框架并将它们与验证算法集成来为深度网络提供类似的集成，以缓解可扩展性挑战并使故障网络的修复成为可能。