<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Flowers on Vladimir Lapin</title><link>https://vlap.github.io/tags/flowers/</link><description>Recent content in Flowers on Vladimir Lapin</description><image><title>Vladimir Lapin</title><url>https://vlap.github.io/images/decor/vladimir_lapin.jpg</url><link>https://vlap.github.io/images/decor/vladimir_lapin.jpg</link></image><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 15 Jun 2026 14:00:00 +0200</lastBuildDate><atom:link href="https://vlap.github.io/tags/flowers/index.xml" rel="self" type="application/rss+xml"/><item><title>Discovering Flowers: Why Multihead Coordinate Warps are a Breakthrough for Neural Fluid Solvers</title><link>https://vlap.github.io/posts/2026-06-15-neural-surrogates-shallow-water-equations/</link><pubDate>Mon, 15 Jun 2026 14:00:00 +0200</pubDate><guid>https://vlap.github.io/posts/2026-06-15-neural-surrogates-shallow-water-equations/</guid><description>When Till Muser shared Flowers—a neural PDE solver built entirely from multihead coordinate warps without Fourier multipliers or attention—it immediately resonated with our CFD background. Here is our experience discovering and benchmarking Flowers on the 2D Shallow Water Equations from PDEBench.</description></item></channel></rss>