no code implementations • 18 Nov 2020 • Dario Guidotti, Luca Pulina, Armando Tacchella
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.
no code implementations • 17 Mar 2020 • Dario Guidotti, Francesco Leofante, Luca Pulina, Armando Tacchella
Verification of deep neural networks has witnessed a recent surge of interest, fueled by success stories in diverse domains and by abreast concerns about safety and security in envisaged applications.
no code implementations • 19 Jun 2018 • Arthur Bit-Monnot, Francesco Leofante, Luca Pulina, Erika Abraham, Armando Tacchella
Smart factories are on the verge of becoming the new industrial paradigm, wherein optimization permeates all aspects of production, from concept generation to sales.
no code implementations • 25 May 2018 • Francesco Leofante, Nina Narodytska, Luca Pulina, Armando Tacchella
Neural networks are one of the most investigated and widely used techniques in Machine Learning.
no code implementations • 24 Feb 2018 • Svyatoslav Korneev, Nina Narodytska, Luca Pulina, Armando Tacchella, Nikolaj Bjorner, Mooly Sagiv
To perform image generation we need to define a mapping from a porous medium to its physical process parameters.
no code implementations • 12 Nov 2017 • Francesco Leofante, Erika Ábrahám, Tim Niemueller, Gerhard Lakemeyer, Armando Tacchella
In manufacturing, the increasing involvement of autonomous robots in production processes poses new challenges on the production management.
no code implementations • 23 Feb 2017 • Marco Menapace, Armando Tacchella
In recent years ontologies enjoyed a growing popularity outside specialized AI communities.