#reservoircomputing
Live, measured metrics for the hashtag #reservoircomputing from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #reservoircomputing
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-29 19:19 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 2026-07-29 19:19 UTCNo related tags with measured usage found for #reservoircomputing.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-29 19:19 UTCEverything below is measured over the latest 20 public posts (spanning ~28487 hours).
Posting hours (UTC) — busiest: 08:00
Languages: English (16) · German (4)
Avg boosts / post: 0.5
Top of the latest posts
This month, CTCS (IIT Madras) & @PIK_climate present a webinar: 📢: Performance-dependent network evolution for enhanced computational capacity 🎙️: Prof. Sudeshna Sinha, IISER Mohali, India 📅: February 23 | 20:30 IST | 16:00 CET | 10:00 E
For #ReservoirComputing lovers,I found a challenging #attractor, the Thomas': dx = np.sin(y) - b * x dy = np.sin(z) - b * y dz = np.sin(x) - b * z x += dx * dt y += dy * dt z += dz * dt 3k neurons yet 67% correlation. Here is the code for y
Li #attractor=chaotic vibes like Lorenz/Chen use its wild dynamics for #ReservoirComputing to process time series. The truth: just use it because it looks cool⚔🏴☠️🌊 def dequan_li(x,y,z): dx = a*(y - x) + y*z dy = b*x - x*z+y dz = c*z + x
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/reservoircomputing