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.

NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks / Guidotti, D., Pulina, L., Tacchella, A.. - (2020).

NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks

Dario Guidotti;Luca Pulina;
2020-01-01

Abstract

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.
2020
FOMLAS 2020
http://arxiv.org/abs/2011.09933v1
Computer Science - Learning; Computer Science - Learning; Computer Science - Software Engineering
arXiv admin note: text overlap with arXiv:2003.07636
NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks / Guidotti, D., Pulina, L., Tacchella, A.. - (2020).
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Guidotti, Dario; Pulina, Luca; Tacchella, Armando
273
3
none
info:eu-repo/semantics/conferenceObject
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/239897
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