Image de couverture de livre

Fast Graph Condensation with Structure-based Neural Tangent Kernel

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Lin, Fan, Wenqi, Li, Jiatong, Ma, Yao, Li, Qing
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Backdoor Graph Condensation
par: Wu, Jiahao, et autres
Publié: (2024)

Divergence of Empirical Neural Tangent Kernel in Classification Problems
par: Yu, Zixiong, et autres
Publié: (2025)

Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
par: Liu, Jingren, et autres
Publié: (2024)

When and Why Adversarial Training Improves PINNs: A Neural Tangent Kernel Perspective
par: Cao, Yuan-dong, et autres
Publié: (2026)

Differential Privacy Mechanisms in Neural Tangent Kernel Regression
par: Gu, Jiuxiang, et autres
Publié: (2024)

NTKMTL: Mitigating Task Imbalance in Multi-Task Learning from Neural Tangent Kernel Perspective
par: Qin, Xiaohan, et autres
Publié: (2025)

Fast Neural Tangent Kernel Alignment, Norm and Effective Rank via Trace Estimation
par: Hazelden, James
Publié: (2025)

The Positivity of the Neural Tangent Kernel
par: Carvalho, Luís, et autres
Publié: (2024)

Permutation-Invariant Graph Partitioning:How Graph Neural Networks Capture Structural Interactions?
par: Hevapathige, Asela, et autres
Publié: (2023)

Dynamic Graph Condensation
par: Chen, Dong, et autres
Publié: (2025)

GLProtein: Global-and-Local Structure Aware Protein Representation Learning
par: Liu, Yunqing, et autres
Publié: (2025)

Unveiling the Mechanism of Continuous Representation Full-Waveform Inversion: A Wave Based Neural Tangent Kernel Framework
par: Chen, Ruihua, et autres
Publié: (2026)

FastGAS: Fast Graph-based Annotation Selection for In-Context Learning
par: Chen, Zihan, et autres
Publié: (2024)

TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks
par: Liu, Yezi, et autres
Publié: (2024)

Robust Graph Condensation via Classification Complexity Mitigation
par: Luo, Jiayi, et autres
Publié: (2025)

DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis
par: An, Rui, et autres
Publié: (2026)

Score-based Generative Diffusion Models for Social Recommendations
par: Liu, Chengyi, et autres
Publié: (2024)

AKBR: Learning Adaptive Kernel-based Representations for Graph Classification
par: Qian, Feifei, et autres
Publié: (2024)

Path-Coordinated Continual Learning with Neural Tangent Kernel-Justified Plasticity: A Theoretical Framework with Near State-of-the-Art Performance
par: Shit, Rathin Chandra
Publié: (2025)

AscendKernelGen: A Systematic Study of LLM-Based Kernel Generation for Neural Processing Units
par: Cao, Xinzi, et autres
Publié: (2026)

From Semantics to Hierarchy: A Hybrid Euclidean-Tangent-Hyperbolic Space Model for Temporal Knowledge Graph Reasoning
par: Feng, Siling, et autres
Publié: (2024)

Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks
par: Liu, Xuyuan, et autres
Publié: (2024)

Improving Clean Accuracy via a Tangent-Space Perspective on Adversarial Training
par: Yi, Bongsoo, et autres
Publié: (2024)

When Training-Free NAS Meets Vision Transformer: A Neural Tangent Kernel Perspective
par: Zhou, Qiqi, et autres
Publié: (2024)

Graph Condensation: A Survey
par: Gao, Xinyi, et autres
Publié: (2024)

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection
par: Bei, Yuanchen, et autres
Publié: (2024)

A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation
par: Hashemi, Mohammad, et autres
Publié: (2024)

Factor Graph-based Interpretable Neural Networks
par: Li, Yicong, et autres
Publié: (2025)

CKGConv: General Graph Convolution with Continuous Kernels
par: Ma, Liheng, et autres
Publié: (2024)

Dynamic Universal Approximation Theory: Foundations for Parallelism in Neural Networks
par: Wang, Wei, et autres
Publié: (2024)

Graph Attention Networks Unleashed: A Fast and Explainable Vulnerability Assessment Framework for Microgrids
par: Liu, Wei, et autres
Publié: (2025)

Simple Graph Condensation
par: Xiao, Zhenbang, et autres
Publié: (2024)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
par: Fan, Shaohua, et autres
Publié: (2021)

A Fast Kernel-based Conditional Independence test with Application to Causal Discovery
par: Schacht, Oliver, et autres
Publié: (2025)

Hyperbolic Kernel Graph Neural Networks for Neurocognitive Decline Analysis from Multimodal Brain Imaging
par: Yang, Meimei, et autres
Publié: (2025)

Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
par: Wang, Di, et autres
Publié: (2023)

Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction
par: An, Rui, et autres
Publié: (2025)

FastKernels: Benchmarking GPU Kernel Generation in Production
par: Oliaro, Gabriele, et autres
Publié: (2026)

Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting
par: Wu, Lirong, et autres
Publié: (2024)

One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs
par: Liu, Jingzhe, et autres
Publié: (2024)