<?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>Publications on Yuxin Guo | PhD Student at Carnegie Mellon University</title><link>https://yx-guo.github.io/papers/</link><description>Recent content in Publications on Yuxin Guo | PhD Student at Carnegie Mellon University</description><generator>Hugo -- 0.147.2</generator><language>en</language><lastBuildDate>Sat, 09 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://yx-guo.github.io/papers/index.xml" rel="self" type="application/rss+xml"/><item><title>Separating Intrinsic Ambiguity from Estimation Uncertainty in Deep Generative Models for Linear Inverse Problems</title><link>https://yx-guo.github.io/papers/paper6/</link><pubDate>Sat, 09 May 2026 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper6/</guid><description>Separating intrinsic ambiguity from estimation uncertainty in deep generative models for linear inverse problems.</description></item><item><title>Interpreting Neural Combinatorial Optimization via Evolving Programmatic Bottlenecks</title><link>https://yx-guo.github.io/papers/paper8/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper8/</guid><description>Interpreting neural combinatorial optimization via evolving programmatic bottlenecks.</description></item><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>Identifying Neural Biomarkers of Risk-Taking from Intracranial EEG Recordings</title><link>https://yx-guo.github.io/papers/paper2/</link><pubDate>Sun, 01 Jun 2025 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper2/</guid><description>This paper presents a machine learning pipeline for identifying neural biomarkers of risk-taking from intracranial EEG. Published at IEEE Conference on Neural Engineering, 2025.</description></item><item><title>DeepFocus: A Transnasal Approach for Optimized Deep Brain Stimulation of Reward Circuit Nodes</title><link>https://yx-guo.github.io/papers/paper3/</link><pubDate>Sat, 01 Mar 2025 00:00:00 +0000</pubDate><guid>https://yx-guo.github.io/papers/paper3/</guid><description>DeepFocus is an end-to-end simulation and optimization platform integrating physical modeling with ML-driven inverse optimization for deep brain stimulation. Published in Journal of Neural Engineering, 2025.</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></channel></rss>