[IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.

[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"

(NeurIPS 2023 spotlight) Large-scale Dataset Distillation/Condensation, 50 IPC (Images Per Class) achieves the highest 60.8% on original ImageNet-1K val set.

Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)

ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

Official PyTorch Implementation for the "Distilling Datasets Into Less Than One Image" paper.

Awesome Graph Condensation Papers

Code for Backdoor Attacks Against Dataset Distillation

Official implementation to DELT: A Simple Diversity-driven EarlyLate Training for Dataset Distillation which outperforms SOTA top 1-acc by +1.3% and increases diversity per class by +5%

[ICLR 2024] "Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality" by Xuxi Chen*, Yu Yang*, Zhangyang Wang, Baharan Mirzasoleiman

An Efficient Dataset Condensation Plugin and Its Application to Continual Learning. NeurIPS, 2023.

Dataset Distillation on 3D Point Clouds using Gradient Matching

A collection of dataset distillation papers.

Continual Learning code for SRe2L paper (NeurIPS 2023 spotlight)

Code for our paper "Towards Trustworthy Dataset Distillation" (Pattern Recognition 2025)