Guardado en:
| Autores principales: | Lim, Brian Godwin, Lim, Galvin Brice, Tan, Renzo Roel, King, Irwin, Ikeda, Kazushi |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2511.11046 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Contextualized Messages Boost Graph Representations
por: Lim, Brian Godwin, et al.
Publicado: (2024)
por: Lim, Brian Godwin, et al.
Publicado: (2024)
Towards Unsupervised Causal Representation Learning via Latent Additive Noise Model Causal Autoencoders
por: Ong, Hans Jarett J., et al.
Publicado: (2025)
por: Ong, Hans Jarett J., et al.
Publicado: (2025)
Redefining the Shortest Path Problem Formulation of the Linear Non-Gaussian Acyclic Model: Pairwise Likelihood Ratios, Prior Knowledge, and Path Enumeration
por: Ong, Hans Jarett J., et al.
Publicado: (2024)
por: Ong, Hans Jarett J., et al.
Publicado: (2024)
Dynamic Factor Analysis of Price Movements in the Philippine Stock Exchange
por: Lim, Brian Godwin, et al.
Publicado: (2025)
por: Lim, Brian Godwin, et al.
Publicado: (2025)
Graph Unitary Message Passing
por: Qiu, Haiquan, et al.
Publicado: (2024)
por: Qiu, Haiquan, et al.
Publicado: (2024)
Partitioning Message Passing for Graph Fraud Detection
por: Zhuo, Wei, et al.
Publicado: (2024)
por: Zhuo, Wei, et al.
Publicado: (2024)
Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks
por: Lee, Minho, et al.
Publicado: (2024)
por: Lee, Minho, et al.
Publicado: (2024)
'Si'multaneous 'S'patial-'T'emporal Message Passing for Dynamic Graph Representation Learning
por: Roy, Shubhajit, et al.
Publicado: (2026)
por: Roy, Shubhajit, et al.
Publicado: (2026)
Next Level Message-Passing with Hierarchical Support Graphs
por: Vonessen, Carlos, et al.
Publicado: (2024)
por: Vonessen, Carlos, et al.
Publicado: (2024)
Dual-channel Heterophilic Message Passing for Graph Fraud Detection
por: Zhang, Wenxin, et al.
Publicado: (2025)
por: Zhang, Wenxin, et al.
Publicado: (2025)
How Particle System Theory Enhances Hypergraph Message Passing
por: Ma, Yixuan, et al.
Publicado: (2025)
por: Ma, Yixuan, et al.
Publicado: (2025)
MLGIB: Multi-Label Graph Information Bottleneck for Expressive and Robust Message Passing
por: Wu, Chaokai, et al.
Publicado: (2026)
por: Wu, Chaokai, et al.
Publicado: (2026)
Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
por: Geng, Chuqin, et al.
Publicado: (2026)
por: Geng, Chuqin, et al.
Publicado: (2026)
Symbolic Graph Intelligence: Hypervector Message Passing for Learning Graph-Level Patterns with Tsetlin Machines
por: Blakely, Christian D.
Publicado: (2025)
por: Blakely, Christian D.
Publicado: (2025)
Beyond Message Passing: Neural Graph Pattern Machine
por: Wang, Zehong, et al.
Publicado: (2025)
por: Wang, Zehong, et al.
Publicado: (2025)
AGTCNet: A Graph-Temporal Approach for Principled Motor Imagery EEG Classification
por: Lim, Galvin Brice S., et al.
Publicado: (2025)
por: Lim, Galvin Brice S., et al.
Publicado: (2025)
Distributed Conformal Prediction via Message Passing
por: Wen, Haifeng, et al.
Publicado: (2025)
por: Wen, Haifeng, et al.
Publicado: (2025)
Neural-Symbolic Message Passing with Dynamic Pruning
por: Zhang, Chongzhi, et al.
Publicado: (2025)
por: Zhang, Chongzhi, et al.
Publicado: (2025)
Link Prediction with Untrained Message Passing Layers
por: Qarkaxhija, Lisi, et al.
Publicado: (2024)
por: Qarkaxhija, Lisi, et al.
Publicado: (2024)
Are Graph Transformers Necessary? Efficient Long-Range Message Passing with Fractal Nodes in MPNNs
por: Choi, Jeongwhan, et al.
Publicado: (2025)
por: Choi, Jeongwhan, et al.
Publicado: (2025)
Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling
por: Ceni, Andrea, et al.
Publicado: (2025)
por: Ceni, Andrea, et al.
Publicado: (2025)
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs
por: Park, Sejun, et al.
Publicado: (2024)
por: Park, Sejun, et al.
Publicado: (2024)
Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs
por: von Pichowski, Jan, et al.
Publicado: (2024)
por: von Pichowski, Jan, et al.
Publicado: (2024)
HyperGraphX: Graph Transductive Learning with Hyperdimensional Computing and Message Passing
por: Cong, Guojing, et al.
Publicado: (2025)
por: Cong, Guojing, et al.
Publicado: (2025)
Distilling Privileged Information for Dubins Traveling Salesman Problems with Neighborhoods
por: Shin, Min Kyu, et al.
Publicado: (2024)
por: Shin, Min Kyu, et al.
Publicado: (2024)
Message Passing on the Edge: Towards Scalable and Expressive GNNs
por: Barceló, Pablo, et al.
Publicado: (2025)
por: Barceló, Pablo, et al.
Publicado: (2025)
Could Chemical LLMs benefit from Message Passing
por: Xie, Jiaqing, et al.
Publicado: (2024)
por: Xie, Jiaqing, et al.
Publicado: (2024)
BeMap: Balanced Message Passing for Fair Graph Neural Network
por: Lin, Xiao, et al.
Publicado: (2023)
por: Lin, Xiao, et al.
Publicado: (2023)
Protein Secondary Structure Prediction Using 3D Graphs and Relation-Aware Message Passing Transformers
por: Varshney, Disha, et al.
Publicado: (2025)
por: Varshney, Disha, et al.
Publicado: (2025)
PANDA: Expanded Width-Aware Message Passing Beyond Rewiring
por: Choi, Jeongwhan, et al.
Publicado: (2024)
por: Choi, Jeongwhan, et al.
Publicado: (2024)
FnRGNN: Distribution-aware Fairness in Graph Neural Network
por: Park, Soyoung, et al.
Publicado: (2025)
por: Park, Soyoung, et al.
Publicado: (2025)
Training-Free Message Passing for Learning on Hypergraphs
por: Tang, Bohan, et al.
Publicado: (2024)
por: Tang, Bohan, et al.
Publicado: (2024)
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
por: Wang, Yuelin, et al.
Publicado: (2022)
por: Wang, Yuelin, et al.
Publicado: (2022)
Deep Graph Anomaly Detection: A Survey and New Perspectives
por: Qiao, Hezhe, et al.
Publicado: (2024)
por: Qiao, Hezhe, et al.
Publicado: (2024)
Representation Learning on Heterophilic Graph with Directional Neighborhood Attention
por: Lu, Qincheng, et al.
Publicado: (2024)
por: Lu, Qincheng, et al.
Publicado: (2024)
Transformers from Diffusion: A Unified Framework for Neural Message Passing
por: Wu, Qitian, et al.
Publicado: (2024)
por: Wu, Qitian, et al.
Publicado: (2024)
RelGNN: Composite Message Passing for Relational Deep Learning
por: Chen, Tianlang, et al.
Publicado: (2025)
por: Chen, Tianlang, et al.
Publicado: (2025)
PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks
por: Lin, Nan, et al.
Publicado: (2023)
por: Lin, Nan, et al.
Publicado: (2023)
MORE-CLEAR: Multimodal Offline Reinforcement learning for Clinical notes Leveraged Enhanced State Representation
por: Lim, Yooseok, et al.
Publicado: (2025)
por: Lim, Yooseok, et al.
Publicado: (2025)
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting
por: Zhou, Fan, et al.
Publicado: (2024)
por: Zhou, Fan, et al.
Publicado: (2024)
Ejemplares similares
-
Contextualized Messages Boost Graph Representations
por: Lim, Brian Godwin, et al.
Publicado: (2024) -
Towards Unsupervised Causal Representation Learning via Latent Additive Noise Model Causal Autoencoders
por: Ong, Hans Jarett J., et al.
Publicado: (2025) -
Redefining the Shortest Path Problem Formulation of the Linear Non-Gaussian Acyclic Model: Pairwise Likelihood Ratios, Prior Knowledge, and Path Enumeration
por: Ong, Hans Jarett J., et al.
Publicado: (2024) -
Dynamic Factor Analysis of Price Movements in the Philippine Stock Exchange
por: Lim, Brian Godwin, et al.
Publicado: (2025) -
Graph Unitary Message Passing
por: Qiu, Haiquan, et al.
Publicado: (2024)