<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Riemann on Aayush Bajaj's Augmenting Infrastructure</title><link>https://abaj.ai/tags/riemann/</link><description>Recent content in Riemann on Aayush Bajaj's Augmenting Infrastructure</description><generator>Hugo</generator><language>en</language><copyright>© 2026 Aayush Bajaj</copyright><lastBuildDate>Thu, 09 Jul 2026 21:02:13 +1000</lastBuildDate><atom:link href="https://abaj.ai/tags/riemann/index.xml" rel="self" type="application/rss+xml"/><item><title>Single-Variable Calculus</title><link>https://abaj.ai/wiki/mathematics/calculus/svars/</link><pubDate>Thu, 09 Jul 2026 21:02:56 +1000</pubDate><guid>https://abaj.ai/wiki/mathematics/calculus/svars/</guid><description>&lt;p>the calculus of one real variable, assembled in logical order: limits, then continuity and its two workhorse theorems (ivt, evt), then the derivative and the mean value theorem, taylor&amp;rsquo;s theorem with an honest error bound, and finally the riemann integral and both parts of the fundamental theorem. everything downstream — &lt;a
 href="https://abaj.ai/wiki/mathematics/calculus/mvars/"
 
 
>multivariable calculus&lt;/a>, &lt;a
 href="https://abaj.ai/wiki/mathematics/calculus/diff-eqns/"
 
 
>differential equations&lt;/a>, every convergence argument in machine learning — leans on the theorems here. proofs are given where they are short and instructive; the deferred foundations live in &lt;a
 href="https://abaj.ai/wiki/mathematics/analysis/real/"
 
 
>real analysis&lt;/a> (Courant, Richard, 1996).&lt;/p></description></item></channel></rss>