Promoting Distributed Trust in Machine Learning and Computational Simulation

Published: May 1, 2019
Abstract
Policy decisions are increasingly dependent on the outcomes of simulations and/or machine learning models. The ability to share and interact with these outcomes is relevant across multiple fields and is especially critical in the disease modeling community where models are often only accessible and workable to the researchers that generate them. This work presents a blockchain-enabled system that establishes a decentralized trust between parties...
Paper Details
Title
Promoting Distributed Trust in Machine Learning and Computational Simulation
Published Date
May 1, 2019
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