Imagen de Portada

EvoFormer: Learning Dynamic Graph-Level Representations with Structural and Temporal Bias Correction

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhong, Haodi, Zou, Liuxin, Wang, Di, Wang, Bo, Niu, Zhenxing, Wang, Quan
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

NN-Former: Rethinking Graph Structure in Neural Architecture Representation
por: Xu, Ruihan, et al.
Publicado: (2025)

Tensor Graph Convolutional Network for Dynamic Graph Representation Learning
por: Wang, Ling, et al.
Publicado: (2024)

Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
por: Xiong, Jiafeng, et al.
Publicado: (2025)

Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias
por: Shi, Zhihao, et al.
Publicado: (2023)

Time-varying Interaction Graph ODE for Dynamic Graph Representation Learning
por: Wang, Xiaoyi, et al.
Publicado: (2026)

Transformer-Based Multimodal Knowledge Graph Completion with Link-Aware Contexts
por: Ma, Haodi, et al.
Publicado: (2025)

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention
por: Hoang, Van Thuy, et al.
Publicado: (2025)

Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
por: Wang, Di, et al.
Publicado: (2023)

Spatial-temporal Graph Convolutional Networks with Diversified Transformation for Dynamic Graph Representation Learning
por: Wang, Ling, et al.
Publicado: (2024)

A Selective Learning Method for Temporal Graph Continual Learning
por: Liu, Hanmo, et al.
Publicado: (2025)

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

CTRL: Continuous-Time Representation Learning on Temporal Heterogeneous Information Network
por: Li, Chenglin, et al.
Publicado: (2024)

TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning
por: Deng, Gangda, et al.
Publicado: (2024)

PTCL: Pseudo-Label Temporal Curriculum Learning for Label-Limited Dynamic Graph
por: Zhang, Shengtao, et al.
Publicado: (2025)

VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention
por: Zhou, Jingbo, et al.
Publicado: (2026)

EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations
por: Liu, Nuowei, et al.
Publicado: (2024)

Disentangled Generative Graph Representation Learning
por: Hu, Xinyue, et al.
Publicado: (2024)

StateLinFormer: Stateful Training Enhancing Long-term Memory in Navigation
por: Chen, Zhiyuan, et al.
Publicado: (2026)

Fast and Robust Contextual Node Representation Learning over Dynamic Graphs
por: Guo, Xingzhi, et al.
Publicado: (2024)

Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning
por: Su, Guangxin, et al.
Publicado: (2024)

Graph-level Protein Representation Learning by Structure Knowledge Refinement
por: Wang, Ge, et al.
Publicado: (2024)

'Si'multaneous 'S'patial-'T'emporal Message Passing for Dynamic Graph Representation Learning
por: Roy, Shubhajit, et al.
Publicado: (2026)

Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic Graphs
por: Yu, He, et al.
Publicado: (2025)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
por: Wang, Shouju, et al.
Publicado: (2025)

Bi-Level Graph Structure Learning for Next POI Recommendation
por: Wang, Liang, et al.
Publicado: (2024)

Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies
por: Xu, Mingkun, et al.
Publicado: (2024)

EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
por: Kotoge, Rikuto, et al.
Publicado: (2025)

Learning Network Representations with Disentangled Graph Auto-Encoder
por: Fan, Di, et al.
Publicado: (2024)

EvoMesh: Adaptive Physical Simulation with Hierarchical Graph Evolutions
por: Deng, Huayu, et al.
Publicado: (2024)

Graph Propagation Transformer for Graph Representation Learning
por: Chen, Zhe, et al.
Publicado: (2023)

EvoLM: In Search of Lost Language Model Training Dynamics
por: Qi, Zhenting, et al.
Publicado: (2025)

From Complex Dynamics to DynFormer: Rethinking Transformers for PDEs
por: Lai, Pengyu, et al.
Publicado: (2026)

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

Learning When to Act: Interval-Aware Reinforcement Learning with Predictive Temporal Structure
por: Di Gioia, Davide
Publicado: (2026)

DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
por: Chen, Qingfeng, et al.
Publicado: (2025)

HeteroMILE: a Multi-Level Graph Representation Learning Framework for Heterogeneous Graphs
por: Zhang, Yue, et al.
Publicado: (2024)

Semantic-Enhanced Representation Learning for Road Networks with Temporal Dynamics
por: Chen, Yile, et al.
Publicado: (2024)

TFWaveFormer: Temporal-Frequency Collaborative Multi-level Wavelet Transformer for Dynamic Link Prediction
por: Feng, Hantong, et al.
Publicado: (2026)

FedGRec: Dynamic Spatio-Temporal Federated Graph Learning for Secure and Efficient Cross-Border Recommendations
por: Tan, Zhizhong, et al.
Publicado: (2025)

FatigueFormer: Static-Temporal Feature Fusion for Robust sEMG-Based Muscle Fatigue Recognition
por: Zhang, Tong, et al.
Publicado: (2026)