Cover Image

Cayley Graph Propagation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wilson, JJ, Bechler-Speicher, Maya, Veličković, Petar
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Interpretable and Effective Graph Neural Additive Networks
by: Bechler-Speicher, Maya, et al.
Published: (2024)

TREE-G: Decision Trees Contesting Graph Neural Networks
by: Bechler-Speicher, Maya, et al.
Published: (2022)

Graph Neural Networks Use Graphs When They Shouldn't
by: Bechler-Speicher, Maya, et al.
Published: (2023)

On the Utilization of Unique Node Identifiers in Graph Neural Networks
by: Bechler-Speicher, Maya, et al.
Published: (2024)

A Graph Meta-Network for Learning on Kolmogorov-Arnold Networks
by: Bar-Shalom, Guy, et al.
Published: (2026)

Recurrent Aggregators in Neural Algorithmic Reasoning
by: Xu, Kaijia, et al.
Published: (2024)

Billion-Scale Graph Foundation Models
by: Bechler-Speicher, Maya, et al.
Published: (2026)

Depth-Width tradeoffs in Algorithmic Reasoning of Graph Tasks with Transformers
by: Yehudai, Gilad, et al.
Published: (2025)

A General Recipe for Contractive Graph Neural Networks -- Technical Report
by: Bechler-Speicher, Maya, et al.
Published: (2024)

Graph Mixing Additive Networks
by: Bechler-Speicher, Maya, et al.
Published: (2025)

Temporal Graph Rewiring with Expander Graphs
by: Petrović, Katarina, et al.
Published: (2024)

KNARsack: Teaching Neural Algorithmic Reasoners to Solve Pseudo-Polynomial Problems
by: Požgaj, Stjepan, et al.
Published: (2025)

Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum
by: Hordan, Snir, et al.
Published: (2025)

Softmax is not Enough (for Sharp Size Generalisation)
by: Veličković, Petar, et al.
Published: (2024)

Mining Generalizable Activation Functions
by: Vitvitskyi, Alex, et al.
Published: (2026)

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
by: Bechler-Speicher, Maya, et al.
Published: (2025)

Rotary Position Encodings for Graphs
by: Reid, Isaac, et al.
Published: (2025)

NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
by: Panagiotaki, Efimia, et al.
Published: (2024)

Improving LLM Final Representations with Inter-Layer Geometry
by: Ulanovski, Tom, et al.
Published: (2026)

Perplexity Cannot Always Tell Right from Wrong
by: Veličković, Petar, et al.
Published: (2026)

What makes a good feedforward computational graph?
by: Vitvitskyi, Alex, et al.
Published: (2025)

How do LLMs Compute Verbal Confidence
by: Kumaran, Dharshan, et al.
Published: (2026)

Asynchronous Algorithmic Alignment with Cocycles
by: Dudzik, Andrew, et al.
Published: (2023)

Leveraging Classical Algorithms for Graph Neural Networks
by: Wu, Jason, et al.
Published: (2025)

Positional Attention: Expressivity and Learnability of Algorithmic Computation
by: de Luca, Artur Back, et al.
Published: (2024)

Schreier-Coset Graph Propagation
by: Mishra, Aryan, et al.
Published: (2025)

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

Towards Invariance to Node Identifiers in Graph Neural Networks
by: Bechler-Speicher, Maya, et al.
Published: (2025)

Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers
by: Bechler-Speicher, Maya, et al.
Published: (2026)

Identifying Critical Phases for Disease Onset with Sparse Haematological Biomarkers
by: Zerio, Andrea, et al.
Published: (2025)

GraphBench: Next-generation graph learning benchmarking
by: Stoll, Timo, et al.
Published: (2025)

Rethinking Propagation for Unsupervised Graph Domain Adaptation
by: Liu, Meihan, et al.
Published: (2024)

Knowledge Propagation over Conditional Independence Graphs
by: Chajewska, Urszula, et al.
Published: (2023)

Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
by: Cheng, Yao, et al.
Published: (2023)

How Overconfidence in Initial Choices and Underconfidence Under Criticism Modulate Change of Mind in Large Language Models
by: Kumaran, Dharshan, et al.
Published: (2025)

Multi-View Graph Feature Propagation for Privacy Preservation and Feature Sparsity
by: Harari, Etzion, et al.
Published: (2025)

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
by: Gavranović, Bruno, et al.
Published: (2024)

Amplifying human performance in combinatorial competitive programming
by: Veličković, Petar, et al.
Published: (2024)

Oldie but Goodie: Re-illuminating Label Propagation on Graphs with Partially Observed Features
by: Yun, Sukwon, et al.
Published: (2025)

Better Not to Propagate: Understanding Edge Uncertainty and Over-smoothing in Signed Graph Neural Networks
by: Choi, Yoonhyuk, et al.
Published: (2024)