<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>SynapBridge English</title>
    <description>Reviewed English public updates from SynapBridge</description>
    <link>https://synapbridge.org/en/</link>
    <language>en</language>
    <atom:link href="https://synapbridge.org/en/rss.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>A Model That Reads the Flow of Time, Not Just One Moment: Handling Wearable Signals With a Causal TCN</title>
      <description>How a causal TCN reads past windows without future leakage in wearable time series, and what SynapBridge Life&apos;s synthetic/local evaluation has not yet verified.</description>
      <link>https://synapbridge.org/en/records/causal-tcn-for-wearable-sensor-sequences/</link>
      <guid isPermaLink="false">sb_life_dl_causal_tcn_20260831:en</guid>
      <pubDate>Mon, 31 Aug 2026 04:32:38 GMT</pubDate>
      <atom:updated>2026-08-31T04:32:38.083Z</atom:updated>
    </item>
    <item>
      <title>Why Wearable Data Should Be Compared With Personal Baselines First</title>
      <description>Why personal baselines and person-level splits matter in wearable data, with SynapBridge Life&apos;s synthetic/local evaluation and limits around leakage, false alarms, and calibration.</description>
      <link>https://synapbridge.org/en/records/wearable-personal-baselines-before-model-complexity/</link>
      <guid isPermaLink="false">sb_life_ml_personal_baseline_20260831:en</guid>
      <pubDate>Mon, 31 Aug 2026 04:10:37 GMT</pubDate>
      <atom:updated>2026-08-31T04:10:37.931Z</atom:updated>
    </item>
  </channel>
</rss>