Github Trends®
9651 findingsmedian surprise 0.00326window 7 days
UNIT / TREND-MONITOR · REV 2.6
[ 7 days window ]
SOURCE: own snapshots
▲РЕПО НЕТ В ОКНЕ 3D. ПОКАЗАН FINDING ИЗ ОКНА 7D (7 days) — РАНГ #2719.
FINDING #2719 · UNIT ID 454668629
alexfrom0815/Online-3D-BPP-PCT
Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space.
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0123
ENGAGEMENT0.20
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
3% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
4.43
ACCEL
-2.11
RETENTION
17.8%
PEAK 2026-10-11 · FORK-RETENTION 0.0% · 31 STARS / WINDOW

Author Audience

AUDIENCE
321
FOLLOWERS
90
OWNER ★
2,307

Engagement Signals

FORKS
59
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 31 / 31 (DIVERSITY 1.00)

Why This Is A Finding

alexfrom0815/Online-3D-BPP-PCT собрал 31 звёзд за окно, тогда как у автора всего 90 подписчиков — эффективная аудитория ≈ 321. Это даёт surprise-индекс 0.0123 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9651 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00+0.00ABOVE 72%
VELOCITY4.433.14+1.29ABOVE 62%
RETENTION17.8%16.7%+1.1 PPABOVE 51%
FORKS59277-218ABOVE 24%
SURPRISE0.010.00+0.01ABOVE 72%