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NUS-HPC-AI-Lab avatar

NUS-HPC-AI-Lab/PAD

0
View on GitHub↗
21 stars·2 forks·Python·8 views

PAD

Matching-based Dataset Distillation methods can be summarized into two steps:

Features

  • Gradient Trajectory Matching - Prioritizes alignment strategies to improve distillation outcomes.

Star history

Star history chart for nus-hpc-ai-lab/padStar history chart for nus-hpc-ai-lab/pad

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 PAD

These projects share indexed features with PAD. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • georgecazenavette/mtt-distillationgeorgecazenavette avatar

    georgecazenavette/mtt-distillation

    440View on GitHub↗

    This repo contains code for training expert trajectories and distilling synthetic data from our Dataset Distillation by Matching Training Trajectories paper (CVPR 2022). Please see our project page for more results.

    Python
    View on GitHub↗440
  • gzyaftermath/datmGzyAftermath avatar

    GzyAftermath/DATM

    0View on GitHub↗

    Code

    View on GitHub↗0
  • justincui03/teslajustincui03 avatar

    justincui03/tesla

    30View on GitHub↗

    Hello!!! Thanks for checking out our repo and paper! 🍻

    Python
    View on GitHub↗30
  • angusdujw/ftd-distillationAngusDujw avatar

    AngusDujw/FTD-distillation

    40View on GitHub↗

    This repo contains code for training expert trajectories and distilling synthetic data from our Dataset Distillation by FTD paper (CVPR 2023).

    Python
    View on GitHub↗40
Compare all 13 related projects→

Frequently asked questions

What does nus-hpc-ai-lab/pad do?

Matching-based Dataset Distillation methods can be summarized into two steps:

What are the main features of nus-hpc-ai-lab/pad?

The main features of nus-hpc-ai-lab/pad are: Gradient Trajectory Matching.

Which projects share features with nus-hpc-ai-lab/pad?

Projects with overlapping indexed features include: georgecazenavette/mtt-distillation — This repo contains code for training expert trajectories and distilling synthetic data from our Dataset Distillation… gzyaftermath/datm — Code. justincui03/tesla — Hello!!! Thanks for checking out our repo and paper! 🍻. nialiu/att — This repository contains code for training expert trajectories and distilling synthetic data for the paper: Dataset… nus-hpc-ai-lab/edf — In this work, we propose to emphasize discriminative features for dataset distillation in the complex scenario, i.e.… angusdujw/ftd-distillation — This repo contains code for training expert trajectories and distilling synthetic data from our Dataset Distillation…