#熵
Live, measured metrics for the hashtag #熵 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #熵
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-08-26 07:56 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-08-26 07:56 UTCNo related tags with measured usage found for #熵.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-26 07:56 UTCEverything below is measured over the latest 3 public posts (spanning ~13657 hours).
Posting hours (UTC)
Languages: Chinese (Taiwan) (3)
Avg boosts / post: 0
Top of the latest posts
🌘 馬可夫鏈的熵 ➤ 從波茲曼公式推導隨機系統的有序與無序 ✤ https://chillphysicsenjoyer.substack.com/p/the-entropy-of-a-markov-chain 本文探討了物理學中「熵」的概念演變，從克勞修斯的宏觀熱力學定義出發，延伸至波茲曼基於微觀狀態總數的統計學解釋。作者將此物理框架應用於馬可夫鏈，特別是戴森的細胞模型。透過計算系統在達到平衡狀態時各個微觀配置的排列方式，展示瞭如何利用多項式係數與波茲曼公式精確推導出隨機系
🌗 混合體的熵 ➤ 探討機率混合與資訊量 ✤ https://cgad.ski/blog/entropy-of-a-mixture.html 本文探討了混合機率分佈的熵，具體而言，對於兩個機率密度函數 p0 和 p1，以及一個介於 0 到 1 之間的插值因子 λ，考慮混合機率 pλ = (1-λ)p0 + λp1。文章研究了熵 H(pλ) 隨著 λ 的變化而產生的變化，並揭示了熵作為機率函數是凹函數的性質。進一步地，文章探討了 JSD 散度、KL 散度和 χ² 散度如何從
🌗 大型語言模型輸出的熵 ➤ 探討大型語言模型如ChatGPT的輸出熵對模型預測的影響 ✤ https://nikkin.dev/blog/llm-entropy.html 大型語言模型如ChatGPT和Claude在當今世界中變得無處不在。 理解大型語言模型輸出的資訊理論角度。 透過探索熵的觀點來思考概率分佈。 分析模型對下一個令牌的確信程度。以ChatGPT為例，探討熵在輸出中的應用。 + 透過熵的概念探討語言模型的輸出，確實展現了模型的確信度和不確定度。 + 通過研究
#熵 across platforms
every network with a public tag surfaceFollow #熵 straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/熵