#BayesianInference

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

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
31
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 31
0.4
Avg reactions / post
Mastodon · last 31
—
Reddit posts / month
Reddit search
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Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-09-27 23:45 UTC
0
09-21
0
09-22
0
09-23
0
09-24
0
09-25
0
09-26
0
09-27

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mas.to (Mastodon public search API) · fetched 2026-09-27 23:45 UTC

No related tags with measured usage found for #bayesianinference.

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-09-27 23:45 UTC

Everything below is measured over the latest 31 public posts (spanning ~32229 hours).

Top of the latest posts

  • I'm explaining Hamiltonian Monte Carlo in my grad-level stats class tomorrow, so I put together this animation illustrating HMC in one dimension. I find it very soothing. #bayesian #BayesianInference #posterior #stats #r #rlang #statistics

    pmcm@peter_mcmahan♥ 4↻ 12025-02-24 03:42 UTCView post →
  • Our new paper is now out in #JCIM ! BICePs v2.0: Software for Ensemble Reweighting Using Bayesian Inference of Conformational Populations https://doi.org/10.1021/acs.jcim.2c01296 Congrats to Rob Raddi on this paper and for coding this more

    Vincent Voelz@voelzlab♥ 3↻ 22023-04-24 21:04 UTCView post →
  • I'm teaching my first lecture at the new job today, about probabilistic logic programming, probabilistic inference, and (weighted) model counting. Some of the required reading is a paper (https://eccc.weizmann.ac.il/eccc-reports/2003/TR03-0

    Dr. Anna Latour@[email protected]♥ 2↻ 22024-12-18 10:33 UTCView post →

#bayesianinference across platforms

every network with a public tag surface

Follow #bayesianinference 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/bayesianinference