Cover Image

Superposition in Graph Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pertl, Lukas, Xuanyuan, Han, Liò, Pietro
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Will More Expressive Graph Neural Networks do Better on Generative Tasks?
by: Zou, Xiandong, et al.
Published: (2023)

Explaining the Explainers in Graph Neural Networks: a Comparative Study
by: Longa, Antonio, et al.
Published: (2022)

Algebraic Priors for Approximately Equivariant Networks
by: Ali, Riccardo, et al.
Published: (2025)

GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning
by: Sun, Zhongtian, et al.
Published: (2025)

Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
by: Longa, Antonio, et al.
Published: (2023)

Metric Learning for Clifford Group Equivariant Neural Networks
by: Ali, Riccardo, et al.
Published: (2024)

Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification
by: Cornelio, Cristina, et al.
Published: (2025)

Towards Mechanistic Interpretability of Graph Transformers via Attention Graphs
by: El, Batu, et al.
Published: (2025)

How Smoothing is N-simplicial Attention?
by: Dussolle, Alexandre, et al.
Published: (2025)

CALF: Communication-Aware Learning Framework for Distributed Reinforcement Learning
by: Purves, Carlos, et al.
Published: (2026)

KAPLAN: Kolmogorov-Arnold Prognostic Learnable Activation Networks for Survival Analysis
by: Logothetis, Stelios Boulitsakis, et al.
Published: (2026)

Symmetry and Generalisation in Neural Approximations of Renormalisation Transformations
by: Ashworth, Cassidy, et al.
Published: (2025)

MoRE-GNN: Multi-omics Data Integration with a Heterogeneous Graph Autoencoder
by: Wang, Zhiyu, et al.
Published: (2025)

KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis
by: Zuo, Kaiwen, et al.
Published: (2024)

Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves
by: Borgi, Alessio, et al.
Published: (2025)

Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding
by: Jain, Rishabh, et al.
Published: (2026)

Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning
by: Sun, Zhongtian, et al.
Published: (2025)

Neural Algorithmic Reasoning with Multiple Correct Solutions
by: Kujawa, Zeno, et al.
Published: (2024)

GenRec: Generative Sequential Recommendation with Large Language Models
by: Cao, Panfeng, et al.
Published: (2024)

Commute Graph Neural Networks
by: Zhuo, Wei, et al.
Published: (2024)

Superposition Yields Robust Neural Scaling
by: Liu, Yizhou, et al.
Published: (2025)

FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Models
by: Zhu, Max, et al.
Published: (2024)

An end-to-end attention-based approach for learning on graphs
by: Buterez, David, et al.
Published: (2024)

HeterSEED: Semantics-Structure Decoupling for Heterogeneous Graph Learning under Heterophily
by: Li, Xinyi, et al.
Published: (2026)

xAI-Drop: Don't Use What You Cannot Explain
by: De Luca, Vincenzo Marco, et al.
Published: (2024)

TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting
by: Margeloiu, Andrei, et al.
Published: (2024)

Spectro-Riemannian Graph Neural Networks
by: Grover, Karish, et al.
Published: (2025)

Sparsity and Superposition in Mixture of Experts
by: Chaudhari, Marmik, et al.
Published: (2025)

Mathematical Models of Computation in Superposition
by: Hänni, Kaarel, et al.
Published: (2024)

Unveiling Mode Connectivity in Graph Neural Networks
by: Li, Bingheng, et al.
Published: (2025)

MODE: Efficient Time Series Prediction with Mamba Enhanced by Low-Rank Neural ODEs
by: Chen, Xingsheng, et al.
Published: (2026)

Sheaves Reloaded: A Directional Awakening
by: Fiorini, Stefano, et al.
Published: (2025)

How Particle System Theory Enhances Hypergraph Message Passing
by: Ma, Yixuan, et al.
Published: (2025)

On Implications of Scaling Laws on Feature Superposition
by: Katta, Pavan
Published: (2024)

FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
by: Luo, Renqiang, et al.
Published: (2024)

GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
by: Wang, Xiaoqi, et al.
Published: (2022)

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning
by: Zhang, Yuelin, et al.
Published: (2025)

Graphs Unveiled: Graph Neural Networks and Graph Generation
by: Kovács, László, et al.
Published: (2024)

Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks
by: Zhang, Han, et al.
Published: (2025)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)