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A repo for holding example code

active 2023-08-182026-06-09 (UTC)

Complete coverage26,527 / 26,527 hourly files (100%) · 2 absent upstream2023-08-152026-08-24 (UTC)
Events
91
Pushes
5
Pull requests
12
Issues
5
Stars
36
Forks
11

Activity over time

Daily event counts in the loaded window

Line chart, 1027 days from 2023-08-18 to 2026-06-09. Pushes: 5 total, peak 2 in a day. Pull requests: 12 total, peak 5 in a day. Issues: 5 total, peak 2 in a day. Comments: 7 total, peak 3 in a day. Stars: 36 total, peak 1 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
zjost205102
dependabot[bot]6024
yassir1562001
utkarsh09023110471000

Recent activity

Latest issues, pull requests and releases

  • Pull request#19dependabot[bot]2025-05-30 18:20
  • Pull request#18dependabot[bot]2025-04-18 16:23
  • Pull request#17zjost2025-04-03 04:48
  • Pull request#17zjost2025-04-03 04:48
  • Issue comment#15dependabot[bot]2025-04-02 05:08
    Bump torch from 1.5.0 to 2.4.0 in /gcn_citeseer
  • Pull request#15zjost2025-04-02 05:02
  • Pull request#16zjost2025-03-30 23:56
  • Pull request#16zjost2025-03-27 15:10
  • Issue comment#10dependabot[bot]2025-03-20 04:38
    Bump ipython from 7.16.3 to 8.10.0 in /gcn_citeseer
  • Issue comment#9dependabot[bot]2025-03-20 04:38
    Bump numpy from 1.18.1 to 1.22.0 in /gcn_citeseer
  • Issue comment#8dependabot[bot]2025-03-20 04:38
    Bump numpy from 1.17.4 to 1.22.0 in /adversarial_validation
  • Pull request#9zjost2025-03-20 04:38
  • Pull request#10zjost2025-03-20 04:38
  • Pull request#8zjost2025-03-20 04:38
  • Issue#13zjost2025-03-20 04:37
    i have an error in 'Jp = xent(predp, labels).mean() + wd_term'. (IndexError Traceback (most recent call last) Cell In[52], line 1 ----> 1 dW_approx = get_grads((gcn1_out,), sm1, "W", labels, eps=1e-4, wd=opt.wd) 2 db_approx = get_grads((gcn1_out,), sm1, "b", labels, eps=1e-4, wd=opt.wd) Cell In[50], line 16 14 wd_term = wd/2*(cp_flat**2).sum() / labels.shape[0] 15 #print(wd_term) ---> 16 Jp = xent(predp, labels).mean() + wd_term 18 # J(thet
  • Pull request#14zjost2025-03-20 04:37
  • Pull request#14zjost2025-03-20 04:37
  • Issue comment#13yassir1562024-02-27 14:15
    i have an error in 'Jp = xent(predp, labels).mean() + wd_term'. (IndexError Traceback (most recent call last) Cell In[52], line 1 ----> 1 dW_approx = get_grads((gcn1_out,), sm1, "W", labels, eps=1e-4, wd=opt.wd) 2 db_approx = get_grads((gcn1_out,), sm1, "b", labels, eps=1e-4, wd=opt.wd) Cell In[50], line 16 14 wd_term = wd/2*(cp_flat**2).sum() / labels.shape[0] 15 #print(wd_term) ---> 16 Jp = xent(predp, labels).mean() + wd_term 18 # J(thet
  • Issue#13yassir1562024-02-27 14:12
    i have an error in 'Jp = xent(predp, labels).mean() + wd_term'
  • Issue comment#12zjost2023-09-05 18:00
    Why is there no bias in the output of GCN layer and why there is linear layer before softmax implementation?
  • Issue#12zjost2023-09-05 18:00
    Why is there no bias in the output of GCN layer and why there is linear layer before softmax implementation?
  • Issue#11zjost2023-08-29 14:13
    Difficulty in understanding xent function
  • Issue comment#11zjost2023-08-29 14:13
    Difficulty in understanding xent function
  • Issue#11utkarsh09023110472023-08-29 08:53
    Difficulty in understanding xent function

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 36 stars here means stars gained during the window, not the repo's star count.