Scientific Diffusion

Latest research papers

Tensor Decompositions for Signal Processing: Theory, Advances, and Applications
Journal Article

Neriman Tokcan, Shakir Showkat Sofi, Van Tien Pham, Clémence Prévost, Sofiane Kharbech, Baptiste Magnier, Thanh Phuong Nguyen, Yassine Zniyed, Lieven de Lathauwer

In the era of big data, rapid advancements in technology and data collection methods have led to the generation and accessibility of vast amounts of multi-modal, high-dimensional data across a diverse range of disciplines. Tensor methods have emerged as essential tools in…

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Toughness Properties of Arbitrarily Partitionable Graphs
Journal Article

Julien Bensmail

Drawing inspiration from a well-known conjecture of Chv\'atal on a toughness threshold guaranteeing graph Hamiltonicity, we investigate toughness properties of so-called arbitrarily partitionable (AP) graphs, which are those graphs that can be partitioned into arbitrarily many…

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The Harmonious Coloring Game
Journal Article

Cláudia Linhares Sales, Thiago Marcilon, Nicolas Martins, Nicolas Nisse, Rudini Sampaio

A harmonious k-coloring of a graph G is a 2-distance proper k-coloring of its vertices such that each edge is uniquely identified by the colors of its endpoints. Here, we introduce its game version: the harmonious coloring game. In this two-player game, Alice and Bob…

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Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration
Conference Paper

Katie Z Luo, Minh-Quan Dao, Zhenzhen Liu, Mark Campbell, Wei-Lun Chao, Kilian Q Weinberger, Ezio Malis, Vincent Frémont, Bharath Hariharan, Mao Shan, Stewart Worrall, Julie Stephany Berrio Perez

Vehicle-to-everything (V2X) collaborative perception has emerged as a promising solution to address the limitations of single-vehicle perception systems. However, existing V2X datasets are limited in scope, diversity, and quality. To address these gaps, we present \ours{}, a…

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Improving Vulnerable Road-Users Detection through Hybrid Collaborative Perception and Detection Refinement
Conference Paper

Selma Oubouabdellah, Minh-Quan Dao, Ezio Malis, Elwan Héry, Julien Moreau, Vincent Frémont

Ensuring the safety of autonomous vehicles in complex urban environments critically depends on accurate 3D object detection. While LiDAR sensors provide reliable depth information, their effectiveness is limited by sparsity at long distances and occlusions, particularly in…

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On the h-majority dynamics with many opinions
Conference Paper

Francesco d'Amore, Niccolò d'Archivio, George Giakkoupis, Emanuele Natale

We present the first upper bound on the convergence time to consensus of the well-known $h$-majority dynamics with $k$ opinions, in the synchronous setting, for $h$ and $k$ that are both non-constant values. We suppose that, at the beginning of the process, there is some…

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