#matrices

Live, measured metrics for the hashtag #matrices from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #matrices

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.

$110.68/ year · 8-character #name
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3
Uses / 7 days
Mastodon
3
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 40
0.1
Avg reactions / post
Mastodon · last 40

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 18:09 UTC
0
07-21
0
07-22
1
07-23
1
07-24
1
07-25
0
07-26
0
07-27

3 uses by 3 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 2026-07-27 18:09 UTC

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 18:09 UTC

Everything below is measured over the latest 40 public posts (spanning ~18111 hours).

Posting hours (UTC) — busiest: 07:00

00:0012:0023:00

Languages: English (34) · Spanish (3) · French (2)

Avg boosts / post: 0.7

Top of the latest posts

  • Furthermore, she showed that certain stabilising effects of #network #structure can only be reproduced in theoretical #matrices when the underlying distribution of interaction strengths is highly skewed - which is in apparent contradiction

    Dr. Korinna Allhoff@[email protected]112025-05-01 12:36 UTCView post →
  • #Algebra thread 🧵 Which #matrices have an inverse? Singular matrices never have an inverse. When we look at the determinant, the determinant is non-zero for invertible matrices in the same way that non-zero numbers have an inverse. Non-zer

    Eric Maugendre about data@[email protected]102024-09-04 10:02 UTCView post →
  • Data returned by an observation typically is represented as a vector in machine learning. A neural network can be seen as a large collection of linear models. We may represent the inputs and outputs of each layer as vectors, matrices, and t

    Eric Maugendre about data@[email protected]102024-08-27 06:23 UTCView post →

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/matrices