Delaunay Graph: Addressing Over-Squashing and Over-Smoothing Using Delaunay Triangulation
No confident code implementation found for this paper.
No confident code implementation found for this paper.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
M2SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors
Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
Towards Modern Image Manipulation Localization: A Large-Scale Dataset and Novel Methods
Beyond Seen Primitive Concepts and Attribute-Object Compositional Learning
@article{attali2026delaunay,
title = {Delaunay Graph: Addressing Over-Squashing and Over-Smoothing Using Delaunay Triangulation},
author = {Hugo Attali and Davide Buscaldi and Nathalie Pernelle},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:69f2efce2bed7b58c281a601ad290265e5f8bb81},
journal = {ICML 2024 2024}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/69f2efce2bed7b58c281a601ad290265e5f8bb81)