<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/e067603a2acd4a6685eeb52fe8c9ea04&quot; frameborder=&quot;0&quot; width=&quot;1152&quot; height=&quot;864&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>864</height><width>1152</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>864</thumbnail_height><thumbnail_width>1152</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/e067603a2acd4a6685eeb52fe8c9ea04-bbfcb98961e5d723.gif</thumbnail_url><duration></duration><title>Gaussian Process Spatial Alignment Update</title><description>In this video, I share my progress on a Gaussian process spatial alignment algorithm that was developed by Stanford graduate students. I&apos;ve been updating the code to resolve compatibility issues with various Python packages, which is crucial for users to successfully install and publish their papers. Currently, I&apos;m testing different library versions and creating workflows for ongoing compatibility checks. I plan to have weekly tests to ensure everything functions smoothly. Once fully tested, I&apos;ll upload the final version to the main pip website.</description></oembed>