google-research/timesfm — GitHub trend

FINDING #4756 · UNIT ID 793784055

google-research/timesfm

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

[ PYTHON ][ ORG ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.000255

ENGAGEMENT0.42

FRESHNESS1.00

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

0% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

22.00

ACCEL

0.00

RETENTION

0.0%

PEAK 2026-07-14 · FORK-RETENTION 0.0% · 22 STARS / WINDOW

Author Audience

AUDIENCE

86,124

FOLLOWERS

16,653

OWNER ★

264,091

Engagement Signals

FORKS

2,610

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 22 / 22 (DIVERSITY 1.00)

Why This Is A Finding

google-research/timesfm собрал 22 звёзд за окно, тогда как у автора всего 16,653 подписчиков — эффективная аудитория ≈ 86,124. Это даёт surprise-индекс 0.000255 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

Related Findings

RANKS ABOVE 21% OF 6024 FINDINGS

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METRICS IN CONTEXT

MEDIAN ACROSS ALL 6024 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00-0.00ABOVE 21%

VELOCITY22.009.00+13.00ABOVE 79%

RETENTION0.0%0.0%0.0 PPABOVE 0%

FORKS2,610495+2,115ABOVE 81%

SURPRISE0.000.00-0.00ABOVE 10%