Cover Image

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Galron, Yaniv, Frasca, Fabrizio, Maron, Haggai, Treister, Eran, Eliasof, Moshe
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

Learning from Historical Activations in Graph Neural Networks
by: Galron, Yaniv, et al.
Published: (2026)

GRANOLA: Adaptive Normalization for Graph Neural Networks
by: Eliasof, Moshe, et al.
Published: (2024)

Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT
by: Bar-Shalom, Guy, et al.
Published: (2025)

Global-Local Graph Neural Networks for Node-Classification
by: Eliasof, Moshe, et al.
Published: (2024)

Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs
by: Frasca, Fabrizio, et al.
Published: (2024)

Efficient Subgraph GNNs by Learning Effective Selection Policies
by: Bevilacqua, Beatrice, et al.
Published: (2023)

On The Expressive Power of GNN Derivatives
by: Eitan, Yam, et al.
Published: (2025)

A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
by: Bar-Shalom, Guy, et al.
Published: (2024)

Graph Neural Reaction Diffusion Models
by: Eliasof, Moshe, et al.
Published: (2024)

On The Temporal Domain of Differential Equation Inspired Graph Neural Networks
by: Eliasof, Moshe, et al.
Published: (2024)

An Over Complete Deep Learning Method for Inverse Problems
by: Eliasof, Moshe, et al.
Published: (2024)

Benchmarking Positional Encodings for GNNs and Graph Transformers
by: Grötschla, Florian, et al.
Published: (2024)

Quadratic Binary Optimization with Graph Neural Networks
by: Eliasof, Moshe, et al.
Published: (2024)

Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
by: Southern, Joshua, et al.
Published: (2025)

Efficient GNN Training Through Structure-Aware Randomized Mini-Batching
by: Balaji, Vignesh, et al.
Published: (2025)

Improving the Effective Receptive Field of Message-Passing Neural Networks
by: Finder, Shahaf E., et al.
Published: (2025)

Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations
by: Ben-Yair, Ido, et al.
Published: (2021)

Improving Subgraph-GNNs via Edge-Level Ego-Network Encodings
by: Alvarez-Gonzalez, Nurudin, et al.
Published: (2023)

Neural Message-Passing on Attention Graphs for Hallucination Detection
by: Frasca, Fabrizio, et al.
Published: (2025)

Improved Generalization of Weight Space Networks via Augmentations
by: Shamsian, Aviv, et al.
Published: (2024)

Graph Metanetworks for Processing Diverse Neural Architectures
by: Lim, Derek, et al.
Published: (2023)

Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling
by: Ceni, Andrea, et al.
Published: (2025)

The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
by: Lim, Derek, et al.
Published: (2024)

Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
by: Bar-Shalom, Guy, et al.
Published: (2024)

One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling
by: Berman, Nimrod, et al.
Published: (2025)

Learnable Spatial-Temporal Positional Encoding for Link Prediction
by: Tieu, Katherine, et al.
Published: (2025)

Reversing Large Language Models for Efficient Training and Fine-Tuning
by: Gal, Eshed, et al.
Published: (2025)

Future Directions in the Theory of Graph Machine Learning
by: Morris, Christopher, et al.
Published: (2024)

Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity
by: Eitan, Yam, et al.
Published: (2024)

FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing
by: Elbaz, Ran, et al.
Published: (2025)

GradMetaNet: An Equivariant Architecture for Learning on Gradients
by: Gelberg, Yoav, et al.
Published: (2025)

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

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

Algebraic Positional Encodings
by: Kogkalidis, Konstantinos, et al.
Published: (2023)

Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention
by: Liao, Tongzhou, et al.
Published: (2024)

Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions
by: Bar-Shalom, Guy, et al.
Published: (2025)

Towards Efficient Training of Graph Neural Networks: A Multiscale Approach
by: Gal, Eshed, et al.
Published: (2025)

TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
by: Yi, Lu, et al.
Published: (2025)

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

Efficient Graph Laplacian Estimation by Proximal Newton
by: Medvedovsky, Yakov, et al.
Published: (2023)