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[NeurIPS 2023] code for "DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models

active 2023-10-072025-11-11 (UTC)

Complete coverage26,400 / 26,400 hourly files (100%) · 2 absent upstream2023-08-152026-08-18 (UTC)
Events
119
Pushes
1
Pull requests
2
Issues
19
Stars
68
Forks
10

Activity over time

Daily event counts in the loaded window

Line chart, 767 days from 2023-10-07 to 2025-11-11. Pushes: 1 total, peak 1 in a day. Pull requests: 2 total, peak 2 in a day. Issues: 19 total, peak 3 in a day. Comments: 17 total, peak 4 in a day. Stars: 68 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

Recent activity

Latest issues, pull requests and releases

  • Issue#17babilonio29542025-11-11 20:28
    Problem with pre-trained models
  • Issue comment#12babilonio29542025-11-02 20:50
    Guidance on Using Pretrained Models (ldm.ckpt, autoencoder.ckpt, disdiff.ckpt)
  • Issue#16meongeun2025-03-25 02:06
    Pretrained model files
  • Issue comment#12PuyiYao2025-01-14 07:42
    Guidance on Using Pretrained Models (ldm.ckpt, autoencoder.ckpt, disdiff.ckpt)
  • Issue#15Millielele2024-12-13 03:56
    Could you please upload the taming.modules.vqvae files?
  • Issue comment#12teoaivalis2024-12-03 16:02
    Guidance on Using Pretrained Models (ldm.ckpt, autoencoder.ckpt, disdiff.ckpt)
  • Issue comment#14Sunny-Fresher2024-11-30 12:24
    disdiff.ckpt
  • Issue#14Sunny-Fresher2024-11-30 12:19
    disdiff.ckpt
  • Issue comment#10Sunny-Fresher2024-11-30 11:41
    How can I evaluate trained model with evaluation code?
  • Issue comment#10Sunny-Fresher2024-11-30 11:41
    How can I evaluate trained model with evaluation code?
  • Issue comment#12Sunny-Fresher2024-11-30 11:16
    Guidance on Using Pretrained Models (ldm.ckpt, autoencoder.ckpt, disdiff.ckpt)
  • Pull request#13yu12ki042024-11-28 03:25
  • Pull request#13yu12ki042024-11-28 03:23
  • Issue#12teoaivalis2024-11-12 10:46
    Using Pretrained Models (ldm.ckpt, autoencoder.ckpt, disdiff.ckpt)
  • Issue comment#5WonwoongCho2024-05-13 23:47
    Questions about the pretrained model
  • Issue#11JiajianLu2024-03-28 21:39
    What does the curve look like for dis_loss during training?
  • Issue#10KwanghyeonLee2024-01-31 10:03
    How can I evaluate trained model with evaluation code?
  • Issue#8YChienHung2023-12-07 10:17
    Could you append DisDiff to the diffusers ?
  • Issue comment#7ThomasMrY2023-12-07 08:32
    setup.py not available
  • Issue#7ThomasMrY2023-12-07 08:32
    setup.py not available
  • Issue comment#6ThomasMrY2023-12-07 08:29
    How to manipulate or interpolate images?
  • Issue#5ThomasMrY2023-12-07 08:26
    Questions about the pretrained model
  • Issue#7fraz7112023-11-19 16:23
    setup.py not available
  • Issue#6TakeruShiraishi2023-10-28 11:48
    How to manipulate or interpolate images?
  • Issue#5ZiQ-Li2023-10-23 04:09
    Questions about the pretrained model

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 68 stars here means stars gained during the window, not the repo's star count.