Copertina

EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Guan, Weijie, Wang, Haohui, Kang, Jian, Liu, Lihui, Zhou, Dawei
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
di: Wang, Haohui, et al.
Pubblicazione: (2023)

Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
di: Pang, Tianyu, et al.
Pubblicazione: (2026)

Graph Evidential Learning for Anomaly Detection
di: Wei, Chunyu, et al.
Pubblicazione: (2025)

Evidential Uncertainty Probes for Graph Neural Networks
di: Yu, Linlin, et al.
Pubblicazione: (2025)

Evidential Reasoning Advances Interpretable Real-World Disease Screening
di: Lian, Chenyu, et al.
Pubblicazione: (2026)

Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks
di: Wang, Tuo, et al.
Pubblicazione: (2025)

Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization
di: Wang, Haohui, et al.
Pubblicazione: (2023)

EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
di: Wang, Haohui, et al.
Pubblicazione: (2023)

Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs
di: Sun, Nan, et al.
Pubblicazione: (2025)

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

Rethinking Structure Learning For Graph Neural Networks
di: Zheng, Yilun, et al.
Pubblicazione: (2024)

Fairness-Aware Multi-view Evidential Learning with Adaptive Prior
di: Chen, Haishun, et al.
Pubblicazione: (2025)

Learn from Heterophily: Heterophilous Information-enhanced Graph Neural Network
di: Zheng, Yilun, et al.
Pubblicazione: (2024)

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
di: Huang, Zheng, et al.
Pubblicazione: (2024)

Towards Robust Multimodal Learning in the Open World
di: Huo, Fushuo
Pubblicazione: (2025)

TransNet: Transfer Knowledge for Few-shot Knowledge Graph Completion
di: Liu, Lihui, et al.
Pubblicazione: (2025)

What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
di: Zheng, Yilun, et al.
Pubblicazione: (2024)

LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
di: Zeng, Xinyue, et al.
Pubblicazione: (2025)

Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning
di: Yu, Yang, et al.
Pubblicazione: (2023)

Evidential Physics-Informed Neural Networks
di: Tan, Hai Siong, et al.
Pubblicazione: (2025)

HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations
di: Zhang, Shuaicheng, et al.
Pubblicazione: (2025)

Mildly Conservative Regularized Evaluation for Offline Reinforcement Learning
di: Chen, Haohui, et al.
Pubblicazione: (2025)

Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
di: Liu, Pei, et al.
Pubblicazione: (2024)

Evidential Physics-Informed Neural Networks for Scientific Discovery
di: Tan, Hai Siong, et al.
Pubblicazione: (2025)

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation
di: Chun, Yongchan, et al.
Pubblicazione: (2026)

Uncertainty Estimation by Flexible Evidential Deep Learning
di: Yoon, Taeseong, et al.
Pubblicazione: (2025)

Towards Fair Graph Representation Learning in Social Networks
di: Zhang, Guixian, et al.
Pubblicazione: (2024)

Equivariant Evidential Deep Learning for Interatomic Potentials
di: Wang, Zhongyao, et al.
Pubblicazione: (2026)

Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation
di: Jing, Baoyu, et al.
Pubblicazione: (2024)

EviDep: Trustworthy Multimodal Depression Estimation via Disentangled Evidential Learning
di: Liu, Fangyuan, et al.
Pubblicazione: (2026)

Explainable Evidential Clustering
di: de Souza, Victor F. Lopes, et al.
Pubblicazione: (2025)

Simple Graph Contrastive Learning via Fractional-order Neural Diffusion Networks
di: Zhao, Yanan, et al.
Pubblicazione: (2025)

Calibrating LLMs with Information-Theoretic Evidential Deep Learning
di: Li, Yawei, et al.
Pubblicazione: (2025)

Uncertainty Estimation by Density Aware Evidential Deep Learning
di: Yoon, Taeseong, et al.
Pubblicazione: (2024)

Learning Structural Hardness for Combinatorial Auctions: Instance-Dependent Algorithm Selection via Graph Neural Networks
di: Kang, Sungwoo
Pubblicazione: (2026)

Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
di: Barker, Charmaine, et al.
Pubblicazione: (2025)

Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning
di: Wang, Daixin, et al.
Pubblicazione: (2024)

FlowX: Towards Explainable Graph Neural Networks via Message Flows
di: Gui, Shurui, et al.
Pubblicazione: (2022)

Open World Learning Graph Convolution for Latency Estimation in Routing Networks
di: Jin, Yifei, et al.
Pubblicazione: (2022)

Multi-Path Collaborative Reasoning via Reinforcement Learning
di: Lv, Jindi, et al.
Pubblicazione: (2025)