LibAUC: A Deep Learning Library for X-Risk Optimization
active 2024-08-09 → 2026-06-24 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 685 days from 2024-08-09 to 2026-06-24. Pushes: 16 total, peak 4 in a day. Pull requests: 3 total, peak 3 in a day. Issues: 11 total, peak 4 in a day. Comments: 10 total, peak 2 in a day. Stars: 17 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
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| optmai | 13 | 2 | 0 | 4 |
| PenGuln | 9 | 6 | 3 | 0 |
| GangLii | 6 | 5 | 0 | 1 |
| xywei00 | 2 | 2 | 0 | 0 |
| RickeyBorges | 2 | 0 | 0 | 1 |
| Innoversa | 2 | 0 | 0 | 1 |
| LiGuo12 | 1 | 0 | 0 | 1 |
| zhang090210 | 1 | 0 | 0 | 1 |
| lynn94874 | 1 | 1 | 0 | 0 |
| CaptainSxy | 1 | 0 | 0 | 0 |
| Michael-H777 | 1 | 0 | 0 | 0 |
| JerryZ01728 | 1 | 0 | 0 | 1 |
Recent activity
Latest issues, pull requests and releases
- Issue#71optmai2026-03-03 18:00Questions on balanced data
- Issue#38optmai2026-03-03 18:00初次了解到LibAUC，希望向您请教几个问题
- Issue#36optmai2026-03-03 18:00mAUCMLoss for multi-label classification when bs=1 loss return 0
- Issue#35optmai2026-03-03 18:00Question on implementation of AUC Margin Loss
- Issue comment#71optmai2025-09-03 16:55Questions on balanced data
- Issue comment#70optmai2025-08-11 13:47It is recommended to remove the "device" parameter from the code
- Issue#70optmai2025-08-11 13:46It is recommended to remove the "device" parameter from the code
- Issue comment#70zhang0902102025-08-02 19:18It is recommended to remove the "device" parameter from the code
- Issue comment#67optmai2025-01-16 02:03Some confusions about AUCM loss
- Issue comment#68Innoversa2025-01-11 01:24Cannot replicate example on MultiLabelAUCMLoss
- Issue#68Innoversa2025-01-11 01:22Cannot replicate example on MultiLabelAUCMLoss
- Issue comment#67RickeyBorges2025-01-08 04:05Some confusions about AUCM loss
- Issue#67RickeyBorges2025-01-03 08:32Some confusions about AUCM loss
- Issue comment#66LiGuo122024-09-24 23:21Pre-trained weights
- Issue#65optmai2024-09-24 21:51support for segmentation
- Issue comment#66optmai2024-09-24 21:51Pre-trained weights
- Issue#64optmai2024-09-15 19:01Could you please provide an example about how to resume training?
- Issue comment#64GangLii2024-09-13 02:26Could you please provide an example about how to resume training?
- Issue#65Michael-H7772024-09-05 21:19support for segmentation
- Issue#64CaptainSxy2024-09-05 06:36Could you please provide an example about how to resume training?
- Issue comment#31JerryZ017282024-08-29 07:51Using AUCM_MultiLabel for multi-class classification but found the loss returns 0
- ReleasePenGuln2024-08-09 21:25LibAUC 1.4.0
- Pull request#63PenGuln2024-08-09 20:29
- Pull request#62PenGuln2024-08-09 20:13
- Pull request#62PenGuln2024-08-09 19:09
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 17 stars here means stars gained during the window, not the repo's star count.