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MIV-XJTU avatar

MIV-XJTU/CUDD

0
View on GitHub↗
4 stars·1 fork·Python·10 views

CUDD

Zhiheng Ma , Anjia Cao , Funing Yang , Yihong Gong , Xing Wei

Features

  • Decoupled Distillation - Implements curriculum-based strategies for dataset distillation.

Star history

Star history chart for miv-xjtu/cuddStar history chart for miv-xjtu/cudd

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with CUDD

These projects share indexed features with CUDD. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • becarefulofyournaoke/bpsB

    BeCarefulOfYournaoke/BPS

    0View on GitHub↗

    This repo contains PyTorch implementation of Balanced Dataset Distillation via Modeling Multiple Visual Pattern Distribution (BPS, CVPR 2026). BPS produces a pattern-balanced condensed dataset via modeling the multiple visual pattern distribution within each class. This repo contains code for…

    View on GitHub↗0
  • brian-moser/prismBrian-Moser avatar

    Brian-Moser/prism

    1View on GitHub↗

    Official PyTorch implementation of paper (TMLR'26) PRISM : Diversifying Dataset Distillation by Decoupling Architectural Priors.

    Python
    View on GitHub↗1
  • dil-iith/direDIL-IITH avatar

    DIL-IITH/DiRe

    1View on GitHub↗

    Code for WACV 2026 paper "DiRe: Diversity-promoting Regularization for Dataset Condensation"

    Python
    View on GitHub↗1
  • angusdujw/diversity-driven-synthesisAngusDujw avatar

    AngusDujw/Diversity-Driven-Synthesis

    8View on GitHub↗

    The sharp increase in data-related expenses has motivated research into condensing datasets while retaining the most informative features. Dataset distillation has thus recently come to the fore. This paradigm generates synthetic datasets that are representative enough to replace the original…

    Python
    View on GitHub↗8
Compare all 12 related projects→

Frequently asked questions

What does miv-xjtu/cudd do?

Zhiheng Ma , Anjia Cao , Funing Yang , Yihong Gong , Xing Wei

What are the main features of miv-xjtu/cudd?

The main features of miv-xjtu/cudd are: Decoupled Distillation.

Which projects share features with miv-xjtu/cudd?

Projects with overlapping indexed features include: angusdujw/diversity-driven-synthesis — The sharp increase in data-related expenses has motivated research into condensing datasets while retaining the most… becarefulofyournaoke/bps — This repo contains PyTorch implementation of Balanced Dataset Distillation via Modeling Multiple Visual Pattern… brian-moser/prism — Official PyTorch implementation of paper (TMLR'26) PRISM : Diversifying Dataset Distillation by Decoupling… dil-iith/dire — Code for WACV 2026 paper "DiRe: Diversity-promoting Regularization for Dataset Condensation". jiacheng8/cv-dd — Jiacheng Cui, Zhaoyi Li, Xiaochen Ma, Xinyue Bi, Yaxin Luo, Zhiqiang Shen. jiacheng8/fadrm — Fast and Accurate Data Residual Matching for Dataset Distillation.