Results 21 to 30 of about 147 (114)

The significance of structural rich club hubs for the processing of hierarchical stimuli. [PDF]

Hum Brain Mapp
We collected functional magnetic resonance imaging data during presentation of hierarchically structured stimuli, and diffusion weighted imaging data to identify the hierarchical rich club architecture in the same subjects. Integrating functional and structural data revealed an anterior‐medial frontal shift and engagement of rich club hubs for ...
Mecklenbrauck F, Gruber M, Siestrup S, Zahedi A, Grotegerd D, Mauritz M, Trempler I, Dannlowski U, Schubotz RI.   +8 more
europepmc   +2 more sources

An Algorithm for the Exact Treedepth Problem

CoRR, 2020
14 pages, 6 figures, 2 tables. This is an extended version of a paper to appear in the proceedings of SEA 2020. The arXiv version is the conference version plus Appendix A (a correctness proof)
openaire   +4 more sources

Sallow: a heuristic algorithm for treedepth decompositions

CoRR, 2020
We describe a heuristic algorithm for computing treedepth decompositions, submitted for the PACE 2020 challenge. It relies on a variety of greedy algorithms computing elimination orderings, as well as a Divide & Conquer approach on balanced cuts obtained using a from-scratch reimplementation of the 2016 FlowCutter algorithm by Hamann & Strasser
openaire   +5 more sources

SAT-Encodings for Treecut Width and Treedepth [PDF]

, 2019
In this paper we propose, implement, and test the first practical decomposition algorithms for the width parameters treecut width and treedepth. These two parameters have recently gained a lot of attention in the theoretical research community as they offer the algorithmic advantage over treewidth by supporting so-called fixed-parameter algorithms for ...
Robert Ganian, Neha Lodha, Sebastian Ordyniak, Stefan Szeider   +3 more
openaire   +4 more sources

Clustered colouring of graph classes with bounded treedepth or pathwidth

Combinatorics, Probability and Computing, 2022
AbstractThe clustered chromatic number of a class of graphs is the minimum integer $k$ such that for some integer $c$ every graph in the class is $k$ -colourable with monochromatic components of size at most $c$ . We determine the clustered chromatic number of any minor-closed class with bounded treedepth, and prove a best possible upper bound on
Norin, S, Scott, A, Wood, DR
openaire   +2 more sources

Local certification of MSO properties for bounded treedepth graphs

CoRR, 2021
The graph model checking problem consists in testing whether an input graph satisfies a given logical formula. In this paper, we study this problem in a distributed setting, namely local certification. The goal is to assign labels to the nodes of a network to certify that some given property is satisfied, in such a way that the labels can be checked ...
Nicolas Bousquet 0001, Laurent Feuilloley, Théo Pierron   +2 more
openaire   +2 more sources

Hamiltonian Cycle Parameterized by Treedepth in Single Exponential Time and Polynomial Space [PDF]

SIAM Journal on Discrete Mathematics, 2020
Presented at WG2020.
Jesper Nederlof, Michal Pilipczuk, Céline M. F. Swennenhuis, Karol Wegrzycki   +3 more
openaire   +8 more sources

An Improved Time-Efficient Approximate Kernelization for Connected Treedepth Deletion Set

CoRR, 2022
We study the CONNECTED η-TREEDEPTH DELETION problem where the input instance is an undireted graph G = (V, E) and an integer k. The objective is to decide if G has a set S \subseteq V(G) of at most k vertices such that G - S has treedepth at most ηand G[S] is connected.
Eduard Eiben, Diptapriyo Majumdar, M. S. Ramanujan 0001   +2 more
openaire   +2 more sources

Linear Versus Centred Colouring via Pseudogrids

Journal of Graph Theory, EarlyView.
ABSTRACT A centred colouring of a graph is a vertex colouring in which every connected subgraph contains a vertex whose colour is unique and a linear colouring is a vertex colouring in which every (not‐necessarily induced) path contains a vertex whose colour is unique. For a graph G $G$, the centred chromatic number χ cen ( G ) ${\chi }_{\text{cen}}(G)$
Prosenjit Bose, Vida Dujmović, Hussein Houdrouge, Mehrnoosh Javarsineh, Pat Morin   +4 more
wiley   +1 more source

Addressing Bias in Non‐Probability Fisheries Surveys Using Multilevel Regression and Poststratification Approaches

Fish and Fisheries, EarlyView.
ABSTRACT Quantifying harvest of fish stocks is challenging as census data are often unavailable, so surveys are required. Traditional probability‐based surveys use random sampling to obtain representative data that can be scaled to estimate total impact.
Zachary Radford, Wendy Edwards, Samantha Hook, Bridgid Bell, Rebecca Mills, Grace Farrell, Martin J. Genner, Stephen D. Simpson, Kieran Hyder   +8 more
wiley   +1 more source