Cover Image

Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Shenzhi, Liang, Bin, Liu, An, Gui, Lin, Yao, Xingkai, Zhang, Xiaofang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

NodeReg: Mitigating the Imbalance and Distribution Shift Effects in Semi-Supervised Node Classification via Norm Consistency
by: Yang, Shenzhi, et al.
Published: (2025)

Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
by: Yao, Xinhao, et al.
Published: (2024)

Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
by: Chen, Yuhan, et al.
Published: (2025)

Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs
by: Ding, Pengfei, et al.
Published: (2024)

Feature Bank Enhancement for Distance-based Out-of-Distribution Detection
by: Liu, Yuhang, et al.
Published: (2025)

GOODAT: Towards Test-time Graph Out-of-Distribution Detection
by: Wang, Luzhi, et al.
Published: (2024)

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

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

Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection
by: Sun, Li, et al.
Published: (2026)

SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
by: Ding, Zhihao, et al.
Published: (2023)

HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection
by: He, Junwei, et al.
Published: (2024)

Enhancing Heterogeneous Knowledge Graph Completion with a Novel GAT-based Approach
by: Wei, Wanxu, et al.
Published: (2024)

ERIS: An Energy-Guided Feature Disentanglement Framework for Out-of-Distribution Time Series Classification
by: Wu, Xin, et al.
Published: (2025)

Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
by: Yang, Shenzhi, et al.
Published: (2025)

Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks
by: Wang, Zhili, et al.
Published: (2023)

Beyond Johnson-Lindenstrauss: Uniform Bounds for Sketched Bilinear Forms
by: Deb, Rohan, et al.
Published: (2025)

A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View
by: Ma, Jing
Published: (2024)

Dual-channel Heterophilic Message Passing for Graph Fraud Detection
by: Zhang, Wenxin, et al.
Published: (2025)

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

From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
by: Jiang, Xitai, et al.
Published: (2026)

Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
by: Wu, Jiayun, et al.
Published: (2024)

Taming False Positives in Out-of-Distribution Detection with Human Feedback
by: Vishwakarma, Harit, et al.
Published: (2024)

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

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

Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning
by: Wang, Zixu, et al.
Published: (2024)

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

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024)

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

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

Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models
by: Wu, Dennis, et al.
Published: (2024)

Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline
by: Li, Shuhao, et al.
Published: (2024)

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
by: Peng, Bo, et al.
Published: (2024)

Can In-context Learning Really Generalize to Out-of-distribution Tasks?
by: Wang, Qixun, et al.
Published: (2024)

Proficient Graph Neural Network Design by Accumulating Knowledge on Large Language Models
by: Wang, Jialiang, et al.
Published: (2024)

Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning
by: Wang, Yiming, et al.
Published: (2024)

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection
by: Bei, Yuanchen, et al.
Published: (2024)

Label-based Graph Augmentation with Metapath for Graph Anomaly Detection
by: Kim, Hwan, et al.
Published: (2023)

Out-of-Distribution Detection using Counterfactual Distance
by: Stoica, Maria, et al.
Published: (2025)

Probabilistic Trust Intervals for Out of Distribution Detection
by: Singh, Gagandeep, et al.
Published: (2021)

DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning
by: Lu, Yao, et al.
Published: (2025)