Copertina

Core Knowledge Learning Framework for Graph Adaptation and Scalability Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Bowen, Huang, Zhichao, Dai, Genan, Xu, Guangning, Fan, Xiaomao, Huang, Hu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Geometry-Aware Spiking Graph Neural Network
di: Zhang, Bowen, et al.
Pubblicazione: (2025)

ToPT: Task-Oriented Prompt Tuning for Urban Region Representation Learning
di: Guo, Zitao, et al.
Pubblicazione: (2026)

Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning
di: Wang, Yingxu, et al.
Pubblicazione: (2025)

Graph Attention-based Adaptive Transfer Learning for Link Prediction
di: Lu, Huashen, et al.
Pubblicazione: (2025)

Knowledge Probing for Graph Representation Learning
di: Zhao, Mingyu, et al.
Pubblicazione: (2024)

Fairness in Graph Learning Augmented with Machine Learning: A Survey
di: Luo, Renqiang, et al.
Pubblicazione: (2025)

Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction
di: Zhang, Bowen, et al.
Pubblicazione: (2024)

Reinforcement Learning for Scalable Train Timetable Rescheduling with Graph Representation
di: Yue, Peng, et al.
Pubblicazione: (2024)

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs
di: Radwan, Yousef A., et al.
Pubblicazione: (2026)

Scalable Heterogeneous Graph Learning via Heterogeneous-aware Orthogonal Prototype Experts
di: Zhou, Wei, et al.
Pubblicazione: (2026)

SMART: Relation-Aware Learning of Geometric Representations for Knowledge Graphs
di: Amouzouvi, Kossi, et al.
Pubblicazione: (2025)

Subgoal Graph-Augmented Planning for LLM-Guided Open-World Reinforcement Learning
di: Fan, Shanwei, et al.
Pubblicazione: (2025)

DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation
di: Yan, Yang, et al.
Pubblicazione: (2026)

Shape-aware Graph Spectral Learning
di: Xu, Junjie, et al.
Pubblicazione: (2023)

Scalable Graph Self-Supervised Learning
di: Pasand, Ali Saheb, et al.
Pubblicazione: (2024)

GraphSeqLM: A Unified Graph Language Framework for Omic Graph Learning
di: Zhang, Heming, et al.
Pubblicazione: (2024)

TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning
di: E, Jiawei, et al.
Pubblicazione: (2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
di: Younesian, Taraneh, et al.
Pubblicazione: (2023)

Robust Knowledge Transfer in Tiered Reinforcement Learning
di: Huang, Jiawei, et al.
Pubblicazione: (2023)

Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning
di: Guo, Jinjin, et al.
Pubblicazione: (2026)

Learning Structure-Semantic Evolution Trajectories for Graph Domain Adaptation
di: Chen, Wei, et al.
Pubblicazione: (2026)

Multimodal Representation Learning using Adaptive Graph Construction
di: Huang, Weichen
Pubblicazione: (2024)

CMKL: Modality-Aware Continual Learning for Evolving Biomedical Knowledge Graphs
di: Radwan, Yousef A., et al.
Pubblicazione: (2026)

AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning
di: Xu, Fan, et al.
Pubblicazione: (2026)

CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning
di: Sun, Jinze, et al.
Pubblicazione: (2024)

Neural Probabilistic Logic Learning for Knowledge Graph Reasoning
di: Sun, Fengsong, et al.
Pubblicazione: (2024)

GraphEdit: Large Language Models for Graph Structure Learning
di: Guo, Zirui, et al.
Pubblicazione: (2024)

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation
di: Song, Yu, et al.
Pubblicazione: (2025)

Prompt-Based Spatio-Temporal Graph Transfer Learning
di: Hu, Junfeng, et al.
Pubblicazione: (2024)

PyG 2.0: Scalable Learning on Real World Graphs
di: Fey, Matthias, et al.
Pubblicazione: (2025)

Learning Multi-graph Structure for Temporal Knowledge Graph Reasoning
di: Zhang, Jinchuan, et al.
Pubblicazione: (2023)

GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation
di: Guo, Zihao, et al.
Pubblicazione: (2025)

Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
di: Wu, Liming, et al.
Pubblicazione: (2024)

SCL-GNN: Towards Generalizable Graph Neural Networks via Spurious Correlation Learning
di: Zhang, Yuxiang, et al.
Pubblicazione: (2026)

Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning
di: Korkmaz, Ezgi
Pubblicazione: (2026)

ID-MixGCL: Identity Mixup for Graph Contrastive Learning
di: Zhang, Gehang, et al.
Pubblicazione: (2023)

Directed Acyclic Graph Structure Learning from Dynamic Graphs
di: Fan, Shaohua, et al.
Pubblicazione: (2022)

S2FGL: Spatial Spectral Federated Graph Learning
di: Tan, Zihan, et al.
Pubblicazione: (2025)

Automated Knowledge Graph Learning in Industrial Processes
di: Ammann, Lolitta, et al.
Pubblicazione: (2024)

EPLKG: Efficient Prompt Learning with Knowledge Graph
di: Lim, YongTaek, et al.
Pubblicazione: (2023)