<html>
  <head>
    <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
  </head>
  <body text="#000000" bgcolor="#FFFFFF">
    <p>Dear all,</p>
    <p>On Thursday (4th October) at 2pm in <span class="event-where">54
        / 7035 (7B), we have an S3RI seminar from Chris Oates (Newcastle
        University) on </span><span class="event-where"><span
          class="event-description">"</span></span><span
        class="event-where"><span class="event-description"><span
            class="event-description"><span class="event-description">Bayesian
              Probabilistic Numerical Methods</span></span>". Details
          are given below.<br>
        </span></span></p>
    <p><span class="event-where"><span class="event-description"><span><span
              class="event-description">The talk will be followed by tea
              and cake in the staff reading room on level 4 of building
              54. </span></span></span></span></p>
    <p><span class="event-where"><span class="event-description"><span><span
              class="event-description">All are welcome!</span></span></span></span></p>
    <p><span class="event-where"><span class="event-description"><span>Best
            wishes,</span></span></span></p>
    <p><span class="event-where"><span class="event-description"><span>Helen</span></span></span></p>
    <span class="event-details-label"></span><span
      class="event-description">Bayesian Probabilistic Numerical Methods
      <br>
      <br>
      Chris Oates, Newcastle University <br>
      <br>
      The scale and complexity of modern scientific computer codes
      typically precludes a detailed analysis of how the code is
      numerically implemented. For example, multi-scale and
      multi-physics models of the human heart call on diverse numerical
      sub-routines to integrate differential equations, perform
      interpolation and optimise over some parameters of the model. As
      such, the computer output is acknowledged to be inexact and some
      alternative form of uncertainty quantification is needed for the
      output to be properly interpreted. This talk will provide an
      introduction to Bayesian probabilistic numerical methods, which
      aim to provide probabilistic uncertainty quantification for
      computer code output. These methods are composed of "modules" and
      recent work on a novel module for the iterative solution of large
      linear systems will be presented in detail.</span><br>
    <br>
    <span class="event-where"><span class="event-description"><span><span
            class="event-description"><span> <span
                class="event-description"> </span><span
                class="event-description"><span
                  class="event-description">For the current schedule of
                  S3RI seminars, see <a class="moz-txt-link-freetext"
                    href="https://tinyurl.com/s3riseminar">https://tinyurl.com/s3riseminar</a>
                </span></span></span></span></span></span></span><br>
    <p><span class="event-where"><span class="event-description"><span><span
              class="event-description"></span></span></span></span></p>
  </body>
</html>