Copertina

Learning Efficient Positional Encodings with Graph Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kanatsoulis, Charilaos I., Choi, Evelyn, Jegelka, Stephanie, Leskovec, Jure, Ribeiro, Alejandro
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

RelGNN: Composite Message Passing for Relational Deep Learning
di: Chen, Tianlang, et al.
Pubblicazione: (2025)

Learning over Positive and Negative Edges with Contrastive Message Passing
di: Pao-Huang, Peter, et al.
Pubblicazione: (2026)

Relational Deep Learning: Challenges, Foundations and Next-Generation Architectures
di: Dwivedi, Vijay Prakash, et al.
Pubblicazione: (2025)

T-GAE: Transferable Graph Autoencoder for Network Alignment
di: He, Jiashu, et al.
Pubblicazione: (2023)

Solving Large-scale Spatial Problems with Convolutional Neural Networks
di: Owerko, Damian, et al.
Pubblicazione: (2023)

Relational Graph Transformer
di: Dwivedi, Vijay Prakash, et al.
Pubblicazione: (2025)

WindMiL: Equivariant Graph Learning for Wind Loading Prediction
di: Vargiemezis, Themistoklis, et al.
Pubblicazione: (2025)

Multi-Target Tracking with Transferable Convolutional Neural Networks
di: Owerko, Damian, et al.
Pubblicazione: (2022)

Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data
di: Ranjan, Rishabh, et al.
Pubblicazione: (2025)

RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
di: Gu, Justin, et al.
Pubblicazione: (2026)

GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts
di: Wu, Shirley, et al.
Pubblicazione: (2023)

Uncalibrated Reasoning: GRPO Induces Overconfidence for Stochastic Outcomes
di: Bereket, Michael, et al.
Pubblicazione: (2025)

On the Stability of Expressive Positional Encodings for Graphs
di: Huang, Yinan, et al.
Pubblicazione: (2023)

Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning
di: Muthusamy, Shreyas, et al.
Pubblicazione: (2024)

Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs
di: Rauchwerger, Levi, et al.
Pubblicazione: (2024)

TimeGraphs: Graph-based Temporal Reasoning
di: Maheshwari, Paridhi, et al.
Pubblicazione: (2024)

Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings
di: Lagesse, Adrien, et al.
Pubblicazione: (2025)

Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results
di: Tahmasebi, Behrooz, et al.
Pubblicazione: (2020)

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
di: Huang, Qian, et al.
Pubblicazione: (2023)

Size Transferability of Graph Transformers with Convolutional Positional Encodings
di: Porras-Valenzuela, Javier, et al.
Pubblicazione: (2026)

Position: Message-passing and spectral GNNs are two sides of the same coin
di: Vasileiou, Antonis, et al.
Pubblicazione: (2026)

Survey on Generalization Theory for Graph Neural Networks
di: Vasileiou, Antonis, et al.
Pubblicazione: (2025)

Higher-Order Graphon Neural Networks: Approximation and Cut Distance
di: Herbst, Daniel, et al.
Pubblicazione: (2025)

Large Language Models are Good Relational Learners
di: Wu, Fang, et al.
Pubblicazione: (2025)

Learning to Approximate Uniform Facility Location via Graph Neural Networks
di: Qian, Chendi, et al.
Pubblicazione: (2026)

RFG: Test-Time Scaling for Diffusion Large Language Model Reasoning with Reward-Free Guidance
di: Chen, Tianlang, et al.
Pubblicazione: (2025)

Neural Networks With Dense Weights Are Not Universal Approximators
di: Rauchwerger, Levi, et al.
Pubblicazione: (2026)

When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability
di: Luan, Sitao, et al.
Pubblicazione: (2023)

Unrolled Graph Neural Networks for Constrained Optimization
di: Hadou, Samar, et al.
Pubblicazione: (2025)

TGM: a Modular and Efficient Library for Machine Learning on Temporal Graphs
di: Chmura, Jacob, et al.
Pubblicazione: (2025)

RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models
di: Hudovernik, Valter, et al.
Pubblicazione: (2025)

Learning Laplacian Positional Encodings for Heterophilous Graphs
di: Ito, Michael, et al.
Pubblicazione: (2025)

Equivariant Graph Neural Operator for Modeling 3D Dynamics
di: Xu, Minkai, et al.
Pubblicazione: (2024)

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
di: Chang, Serina, et al.
Pubblicazione: (2024)

Representation Learning for Frequent Subgraph Mining
di: Ying, Rex, et al.
Pubblicazione: (2024)

Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
di: Wu, Tailin, et al.
Pubblicazione: (2024)

Are Graph Neural Networks Optimal Approximation Algorithms?
di: Yau, Morris, et al.
Pubblicazione: (2023)

On the Emergence of Position Bias in Transformers
di: Wu, Xinyi, et al.
Pubblicazione: (2025)

KGGen: Extracting Knowledge Graphs from Plain Text with Language Models
di: Mo, Belinda, et al.
Pubblicazione: (2025)

A Manifold Perspective on the Statistical Generalization of Graph Neural Networks
di: Wang, Zhiyang, et al.
Pubblicazione: (2024)