:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Lin, Li, Qing
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2501.02565
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fast Graph Condensation with Structure-based Neural Tangent Kernel
by: Wang, Lin, et al.
Published: (2023)

Backdoor Graph Condensation
by: Wu, Jiahao, et al.
Published: (2024)

Simplifying Graph Kernels for Efficient
by: Wang, Lin, et al.
Published: (2025)

An Efficient and Scalable Graph Condensation with Structure-Preserving
by: Hu, Yulin, et al.
Published: (2026)

Efficient and Privacy-Preserved Link Prediction via Condensed Graphs
by: Long, Yunbo, et al.
Published: (2025)

TCGU: Data-centric Graph Unlearning based on Transferable Condensation
by: Li, Fan, et al.
Published: (2024)

PUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation
by: Liu, Yilun, et al.
Published: (2023)

Graph Random Features for Scalable Gaussian Processes
by: Zhang, Matthew, et al.
Published: (2025)

EXGC: Bridging Efficiency and Explainability in Graph Condensation
by: Fang, Junfeng, et al.
Published: (2024)

HGC-Herd: Efficient Heterogeneous Graph Condensation via Representative Node Herding
by: Ou, Fuyan, et al.
Published: (2025)

Graph Condensation for Open-World Graph Learning
by: Gao, Xinyi, et al.
Published: (2024)

Matérn Gaussian Processes on Graphs
by: Borovitskiy, Viacheslav, et al.
Published: (2020)

Multi-view Graph Condensation via Tensor Decomposition
by: Santos, Nícolas Roque dos, et al.
Published: (2025)

Robust Graph Condensation via Classification Complexity Mitigation
by: Luo, Jiayi, et al.
Published: (2025)

Graph Classification Gaussian Processes via Hodgelet Spectral Features
by: Alain, Mathieu, et al.
Published: (2024)

Intrinsic Gaussian Process Regression Modeling for Manifold-valued Response Variable
by: Wang, Zhanfeng, et al.
Published: (2024)

Simple Graph Condensation
by: Xiao, Zhenbang, et al.
Published: (2024)

GCondenser: Benchmarking Graph Condensation
by: Liu, Yilun, et al.
Published: (2024)

A Survey on Graph Condensation
by: Xu, Hongjia, et al.
Published: (2024)

Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching
by: Zhang, Tianle, et al.
Published: (2024)

Towards Pre-trained Graph Condensation via Optimal Transport
by: Yan, Yeyu, et al.
Published: (2025)

Training-free Heterogeneous Graph Condensation via Data Selection
by: Liang, Yuxuan, et al.
Published: (2024)

Dynamic Graph Condensation
by: Chen, Dong, et al.
Published: (2025)

C$^{2}$TC: A Training-Free Framework for Efficient Tabular Data Condensation
by: Xu, Sijia, et al.
Published: (2026)

Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
by: Zhang, Yuchen, et al.
Published: (2024)

Calibrating Transformers via Sparse Gaussian Processes
by: Chen, Wenlong, et al.
Published: (2023)

Transferable Graph Condensation from the Causal Perspective
by: Du, Huaming, et al.
Published: (2026)

Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck
by: Fu, Xingcheng, et al.
Published: (2024)

Disentangled Condensation for Large-scale Graphs
by: Xiao, Zhenbang, et al.
Published: (2024)

PLGC: Pseudo-Labeled Graph Condensation
by: Nandy, Jay, et al.
Published: (2026)

DANCE: Dynamic, Available, Neighbor-gated Condensation for Federated Text-Attributed Graphs
by: Chen, Zekai, et al.
Published: (2026)

Graph Condensation: A Survey
by: Gao, Xinyi, et al.
Published: (2024)

Graph and Simplicial Complex Prediction Gaussian Process via the Hodgelet Representations
by: Alain, Mathieu, et al.
Published: (2025)

GC-Bench: An Open and Unified Benchmark for Graph Condensation
by: Sun, Qingyun, et al.
Published: (2024)

Enabling On-Device Learning via Experience Replay with Efficient Dataset Condensation
by: Xu, Gelei, et al.
Published: (2024)

On the Usage of Gaussian Process for Efficient Data Valuation
by: Bénesse, Clément, et al.
Published: (2025)

Multi-Output Gaussian Processes for Graph-Structured Data
by: Nakai-Kasai, Ayano, et al.
Published: (2025)

RobGC: Towards Robust Graph Condensation
by: Gao, Xinyi, et al.
Published: (2024)

FairGC: Fairness-aware Graph Condensation
by: Gao, Yihan, et al.
Published: (2026)

Empirical Gaussian Processes
by: Lin, Jihao Andreas, et al.
Published: (2026)