:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Guo, Kai, Wen, Hongzhi, Jin, Wei, Guo, Yaming, Tang, Jiliang, Chang, Yi
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2402.08228
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness
por: Guo, Kai, et al.
Publicado: (2024)

Subgraph Generation for Generalizing on Out-of-Distribution Links
por: Revolinsky, Jay, et al.
Publicado: (2025)

Concept Matching with Agent for Out-of-Distribution Detection
por: Lee, Yuxiao, et al.
Publicado: (2024)

Label-free Node Classification on Graphs with Large Language Models (LLMS)
por: Chen, Zhikai, et al.
Publicado: (2023)

Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks
por: Panda, Deepak Kumar, et al.
Publicado: (2025)

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
por: Chen, Zhikai, et al.
Publicado: (2023)

Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift
por: Wang, Bohan, et al.
Publicado: (2024)

Towards Understanding Link Predictor Generalizability Under Distribution Shifts
por: Revolinsky, Jay, et al.
Publicado: (2024)

Uncovering Graph Reasoning in Decoder-only Transformers with Circuit Tracing
por: Dai, Xinnan, et al.
Publicado: (2025)

Are Expressive Encoders Necessary for Discrete Graph Generation?
por: Revolinsky, Jay, et al.
Publicado: (2026)

How Hard Is It for Message-Passing GNNs to Simulate One Weisfeiler-Lehman Color-Refinement Step?
por: Cui, Guanyu, et al.
Publicado: (2024)

Out-of-Variable Generalization for Discriminative Models
por: Guo, Siyuan, et al.
Publicado: (2023)

Out-of-Distribution Generalization for Neural Physics Solvers
por: Wei, Zhao, et al.
Publicado: (2026)

Sparsity and Out-of-Distribution Generalization
por: Aaronson, Scott, et al.
Publicado: (2026)

Enhancing GNNs with Architecture-Agnostic Graph Transformations: A Systematic Analysis
por: Li, Zhifei, et al.
Publicado: (2024)

Sub-graph Based Diffusion Model for Link Prediction
por: Li, Hang, et al.
Publicado: (2024)

LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
por: Gao, Hang, et al.
Publicado: (2025)

Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model
por: Zhao, Chu, et al.
Publicado: (2025)

Explainable Fuzzy GNNs for Leak Detection in Water Distribution Networks
por: Khaled, Qusai, et al.
Publicado: (2026)

Causal Negative Sampling via Diffusion Model for Out-of-Distribution Recommendation
por: Zhao, Chu, et al.
Publicado: (2025)

Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
por: Shomer, Harry, et al.
Publicado: (2024)

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
por: Wang, Song, et al.
Publicado: (2025)

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
por: Wang, Song, et al.
Publicado: (2025)

Aligning Large Language Models and Geometric Deep Models for Protein Representation
por: Shu, Dong, et al.
Publicado: (2024)

TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
por: Yi, Lu, et al.
Publicado: (2025)

AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
por: Lu, Weigang, et al.
Publicado: (2024)

Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
por: Kaur, Jivat Neet, et al.
Publicado: (2022)

Mean-Field Control on Sparse Graphs: From Local Limits to GNNs via Neighborhood Distributions
por: Schmidt, Tobias, et al.
Publicado: (2026)

Disentangled Interest Network for Out-of-Distribution CTR Prediction
por: Zheng, Yu, et al.
Publicado: (2025)

DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
por: Sun, Xin, et al.
Publicado: (2024)

Out-of-Distribution Generalization in Time Series: A Survey
por: Wu, Xin, et al.
Publicado: (2025)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
por: Fan, Shaohua, et al.
Publicado: (2021)

Hierarchical Source-to-Post-Route QoR Prediction in High-Level Synthesis with GNNs
por: Gao, Mingzhe, et al.
Publicado: (2024)

A Median Perspective on Unlabeled Data for Out-of-Distribution Detection
por: Abbas, Momin, et al.
Publicado: (2025)

SFR-GNN: Simple and Fast Robust GNNs against Structural Attacks
por: Ai, Xing, et al.
Publicado: (2024)

GCoDE: Efficient Device-Edge Co-Inference for GNNs via Architecture-Mapping Co-Search
por: Zhou, Ao, et al.
Publicado: (2025)

STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution Generalization
por: Zhang, Haoyu, et al.
Publicado: (2025)

Learning Multi-Manifold Embedding for Out-Of-Distribution Detection
por: Li, Jeng-Lin, et al.
Publicado: (2024)

Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness-Generalization Perspective
por: Gu, Ming, et al.
Publicado: (2024)

One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs
por: Liu, Jingzhe, et al.
Publicado: (2024)