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Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)

active 2023-09-152026-02-03 (UTC)

Complete coverage26,464 / 26,464 hourly files (100%) · 2 absent upstream2023-08-152026-08-21 (UTC)
Events
58
Pushes
0
Pull requests
0
Issues
1
Stars
53
Forks
2

Activity over time

Daily event counts in the loaded window

Line chart, 873 days from 2023-09-15 to 2026-02-03. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 1 total, peak 1 in a day. Comments: 2 total, peak 1 in a day. Stars: 53 total, peak 3 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
SeanZh301001
thangld2011000
gumityolcu1001

Recent activity

Latest issues, pull requests and releases

  • Issue#11thangld2012024-03-11 11:32
    Q: Applicability to sequence tagging
  • Issue comment#10SeanZh302024-02-25 20:06
    where is the loss gradient calculated in the proponent/opponent example
  • Issue comment#10gumityolcu2024-01-18 14:58
    where is the loss gradient calculated in the proponent/opponent example

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 53 stars here means stars gained during the window, not the repo's star count.