#sparxivdigest
Live, measured metrics for the hashtag #sparxivdigest from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #sparxivdigest
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 · mastodon.social (Mastodon public tags API) · fetched 2026-10-11 15:25 UTCNo measured public usage for #sparxivdigest in the last 7 days. That is a real result, and a good one to know: this hashtag is wide open right now. We show a dash before we ever show a made-up number. Browse the trending index for tags with live measurements.
Related hashtags
measured · mastodon.social (Mastodon public search API) · fetched 2026-10-11 15:25 UTCNo related tags with measured usage found for #sparxivdigest.
Live pulse
measured · mastodon.social (Mastodon tag timeline) · fetched 2026-10-11 15:25 UTCEverything below is measured over the latest 40 public posts (spanning ~2376 hours).
Posting hours (UTC) — busiest: 10:00
Languages: English (40)
Avg boosts / post: 1.3
Used together with
No co-used tags in the sample.
Top of the latest posts
https://arxiv.org/abs/2305.03158 'Quantile Importance Sampling' - Jyotishka Datta, Nicholas G. Polson A number of interesting Monte Carlo procedures are obtained by rewriting an initial integral in terms of the quantile function of the inte
https://arxiv.org/abs/2306.02066 'Variational Gaussian Process Diffusion Processes' - Prakhar Verma, Vincent Adam, Arno Solin One popular approach to approximate inference in partially-observed diffusion processes is variational inference,
https://arxiv.org/abs/2306.01993 'Provable benefits of score matching' - Chirag Pabbaraju, Dhruv Rohatgi, Anish Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski For the large-sample theory of statistical parameter estimation, it is under
#sparxivdigest across platforms
every network with a public tag surfaceFollow #sparxivdigest 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/sparxivdigest