<?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>EEG on Yuxin Guo | PhD Student at Carnegie Mellon University</title><link>https://yx-guo.github.io/tags/eeg/</link><description>Recent content in EEG on Yuxin Guo | PhD Student at Carnegie Mellon University</description><generator>Hugo -- 0.147.2</generator><language>en</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://yx-guo.github.io/tags/eeg/index.xml" rel="self" type="application/rss+xml"/><item><title>Information-theoretic Error Bounds for Source Localization in Neural Sensing</title><link>https://yx-guo.github.io/papers/paper1/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper1/</guid><description>This paper analyzes and quantifies theoretical limits of EEG sensing systems with Fisher information metrics. Accepted at AISTATS, 2026.</description></item><item><title>EEG Source Imaging of Infarct Core and Penumbra for Ischemic Stroke Patients</title><link>https://yx-guo.github.io/papers/paper7/</link><pubDate>Thu, 01 Jun 2023 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper7/</guid><description>EEG source imaging methods for identifying infarct core and penumbra in ischemic stroke patients. Published at IEEE EMBC, 2023.</description></item><item><title>Effects of EEG Electrode Numbers on Deep Learning-Based Source Imaging</title><link>https://yx-guo.github.io/papers/paper4/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper4/</guid><description>This paper studies the effects of EEG electrode density on deep learning-based source imaging methods. Published in Brain Informatics, 2023.</description></item><item><title>Machine Learning for Neural Sensing</title><link>https://yx-guo.github.io/research/research1/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/research/research1/</guid><description>End-to-end machine learning systems for neural sensing, source localization, and biomarker discovery at Carnegie Mellon University.</description></item></channel></rss>