Repository for the Deep Learning II Course @ UvA
active 2024-03-03 → 2026-01-15 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 684 days from 2024-03-03 to 2026-01-15. Pushes: 4 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 8 total, peak 2 in a day. Comments: 13 total, peak 2 in a day. Stars: 29 total, peak 2 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 |
|---|---|---|---|---|
| karrykkk | 9 | 4 | 0 | 5 |
| Lollins7 | 3 | 0 | 0 | 1 |
| LibertyRoamer | 2 | 0 | 0 | 1 |
| cilevanmarken | 2 | 0 | 0 | 2 |
| Allenwannasleep | 2 | 0 | 0 | 1 |
| RyleHan | 1 | 0 | 0 | 1 |
| wanzhe45 | 1 | 0 | 0 | 0 |
| xiexh20 | 1 | 0 | 0 | 1 |
| pikeyang | 1 | 0 | 0 | 0 |
| hejiaxiang1 | 1 | 0 | 0 | 0 |
| a-Fomalhaut-a | 1 | 0 | 0 | 1 |
| JesseWiers | 1 | 0 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue#9wanzhe452026-01-15 09:41The variance tensor contains elements less than 0
- Issue comment#8Allenwannasleep2025-10-16 03:00Hello, thank you for your excellent code. I encountered a problem when running sd: the asdfghjkl module cannot be imported.
- Issue comment#8a-Fomalhaut-a2025-10-15 13:40Hello, thank you for your excellent code. I encountered a problem when running sd: the asdfghjkl module cannot be imported.
- Issue#8Allenwannasleep2025-09-17 08:19Hello, thank you for your excellent code. I encountered a problem when running sd: the asdfghjkl module cannot be imported.
- Issue comment#5RyleHan2025-03-22 05:10the loss dose not decrease with each iteration.
- Issue#7pikeyang2025-03-18 05:55When I trained U-ViT with your code, the output of the model was a pure black graph
- Issue#6Lollins72024-12-10 07:56Can't run BayesDiff/ddpm_and_guided/laplace/curvature/asdl.py
- Issue comment#6Lollins72024-12-10 07:56Can't run BayesDiff/ddpm_and_guided/laplace/curvature/asdl.py
- Issue#6Lollins72024-12-10 07:39Can't run BayesDiff/ddpm_and_guided/laplace/curvature/asdl.py
- Issue comment#1LibertyRoamer2024-05-24 12:52Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue comment#3karrykkk2024-05-20 02:54Pre-trained model checkpoints CELEBA
- Issue comment#1karrykkk2024-05-20 02:39Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue#3JesseWiers2024-05-18 12:32Pre-trained model checkpoints CELEBA
- Issue comment#1cilevanmarken2024-05-18 11:25Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue comment#1karrykkk2024-05-17 10:18Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue comment#2karrykkk2024-05-17 02:54Can this method be used to measure the uncertainty of detail reconstruction?
- Issue comment#1cilevanmarken2024-05-16 13:02Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue#2LibertyRoamer2024-05-10 04:50Can this method be used to measure the uncertainty of detail reconstruction?
- Issue comment#1karrykkk2024-03-26 09:48Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue comment#1xiexh202024-03-22 15:20Can you give the visualization code for the uncertainty estimation for each pixel point?
- Issue#1hejiaxiang12024-03-22 08:10Can you give the visualization code for the uncertainty estimation for each pixel point?
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 29 stars here means stars gained during the window, not the repo's star count.