<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>不确定性估计 on AI 早报</title><link>https://ai-news.example.com/tags/%E4%B8%8D%E7%A1%AE%E5%AE%9A%E6%80%A7%E4%BC%B0%E8%AE%A1/</link><description>Recent content in 不确定性估计 on AI 早报</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Sun, 05 Jul 2026 23:11:14 +0800</lastBuildDate><atom:link href="https://ai-news.example.com/tags/%E4%B8%8D%E7%A1%AE%E5%AE%9A%E6%80%A7%E4%BC%B0%E8%AE%A1/feed.xml" rel="self" type="application/rss+xml"/><item><title>[EN] Google开源AutoBNN：组合贝叶斯神经网络实现可解释时序预测</title><link>https://ai-news.example.com/articles/en-googleautobnn/</link><pubDate>Sun, 05 Jul 2026 23:11:14 +0800</pubDate><guid>https://ai-news.example.com/articles/en-googleautobnn/</guid><description>谷歌发布开源工具AutoBNN，将高斯过程的组合核结构与贝叶斯神经网络的灵活扩展性结合，自动发现可解释的时序预测模型并输出高质量不确定性估计，适用于大规模数据集。</description></item></channel></rss>