<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>JAX on AI 早报</title><link>https://ai-news.example.com/tags/jax/</link><description>Recent content in JAX on AI 早报</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Sat, 04 Jul 2026 06:39:19 +0800</lastBuildDate><atom:link href="https://ai-news.example.com/tags/jax/feed.xml" rel="self" type="application/rss+xml"/><item><title>[EN] AutoBNN：用组合贝叶斯神经网络实现概率时间序列预测</title><link>https://ai-news.example.com/articles/en-autobnn/</link><pubDate>Sat, 04 Jul 2026 06:39:19 +0800</pubDate><guid>https://ai-news.example.com/articles/en-autobnn/</guid><description>谷歌开源了AutoBNN，它结合了传统概率模型的可解释性与神经网络的可扩展性，自动化地发现可解释的时间序列预测模型，并提供高质量的不确定性估计。</description></item></channel></rss>