<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Deep Learning on C2FD</title>
    <link>https://web.iitd.ac.in/~pnair/tags/deep-learning/</link>
    <description>Recent content in Deep Learning on C2FD</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en-us</language>
    <atom:link href="https://web.iitd.ac.in/~pnair/tags/deep-learning/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Flow in complex geometry</title>
      <link>https://web.iitd.ac.in/~pnair/project/project2/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://web.iitd.ac.in/~pnair/project/project2/</guid>
      <description>Characterization of flows in complex geometries Industrial problems are often extremely challenging due to problems involving discrete materials (granular media) and complex shapes (porous media). The issue is two folds: characterization of geometry as well as estabilishing the form-function relationship. We use data science tools such as deep learning and graph networks to understand and model such problems.</description>
    </item>
  </channel>
</rss>
