[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
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Updated
May 13, 2024 - Python
[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
[IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
(NeurIPS 2023 spotlight) Large-scale Dataset Distillation/Condensation, 50 IPC (Images Per Class) achieves the highest 60.8% on original ImageNet-1K val set.
ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
Official PyTorch Implementation for the "Distilling Datasets Into Less Than One Image" paper.
Code for Backdoor Attacks Against Dataset Distillation
An Efficient Dataset Condensation Plugin and Its Application to Continual Learning. NeurIPS, 2023
Dataset Distillation on 3D Point Clouds using Gradient Matching
[ICLR 2024] "Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality" by Xuxi Chen*, Yu Yang*, Zhangyang Wang, Baharan Mirzasoleiman
A collection of dataset distillation papers.
Awesome Graph Condensation Papers
Continual Learning code for SRe2L paper (NeurIPS 2023 spotlight)
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