Uncertainty Quantification in Variational Inequalities

<p>Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models. The primary objective of <b>Uncertainty Quantification in Variational Inequalities: Theory Numerics and Applications</b> is to present a comprehensive treatment of UQ in variational inequalities and some of its generalizations emerging from various network economic and engineering models. Some of the developed techniques also apply to machine learning neural networks and related fields.</p><p>Features</p><ul> <p> </p> <li>First book on UQ in variational inequalities emerging from various network economic and engineering models</li> <p> </p> <li>Completely self-contained and lucid in style</li> <p> </p> <li>Aimed for a diverse audience including applied mathematicians engineers economists and professionals from academia</li> <p> </p> <li>Includes the most recent developments on the subject which so far have only been available in the research literature</li> </ul>