Official implementation of "Efficient Dataset Distillation via Minimax Diffusion".
The main features of vimar-gu/minimaxdiffusion are: Generative Distillation.
Open-source alternatives to vimar-gu/minimaxdiffusion include: 528why/dataset-condensation-with-color-compensation — This is the DC3 framework we proposed. For more details, please see the paper. ayushroy2001/manifoldgd — Wei-Yang Alex Lee ¹ · Rudrasis Chakraborty ² · Vishnu Suresh Lokhande ¹. georgecazenavette/glad — This repo contains code for training expert trajectories and distilling synthetic data from our GLaD paper (CVPR… guang000/generative-dataset-distillation-based-on-diffusion-model — Python >=3.9 - Pytorch >= 1.12.1 - Torchvision >= 0.13.1 - Diffusers == 0.29.2. hatchetproject/cao2 — Official repository for CaO 2 : Rectifying Inconsistencies in Diffusion-Based Dataset Distillation. 2018cx/gadc — For convenience, you can create the Conda virtual environment through:.
This is the DC3 framework we proposed. For more details, please see the paper.
Wei-Yang Alex Lee ¹ · Rudrasis Chakraborty ² · Vishnu Suresh Lokhande ¹
This repo contains code for training expert trajectories and distilling synthetic data from our GLaD paper (CVPR 2023). Please see our project page for more results.
