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Copy file name to clipboardExpand all lines: site/mock-papers.yml
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date: 2008-08-11
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description: >
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This page is a reworking of the original t-SNE article using the Computo template. It aims to help authors submitting to the journal by using some advanced formatting features. We warmly thank the authors of t-SNE and the editor of JMLR for allowing us to use their work to illustrate the Computo spirit.
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doi: ''
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draft: false
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journal: Computo
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pdf: ''
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date: 2008-08-11
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description: >
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This page is a reworking of the original t-SNE article using the Computo template. It aims to help authors submitting to the journal by using some advanced formatting features. We warmly thank the authors of t-SNE and the editor of JMLR for allowing us to use their work to illustrate the Computo spirit.
Copy file name to clipboardExpand all lines: site/published.yml
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authors: Julien Jacques and Thomas Brendan Murphy
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date: 2025-07-01
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description: ''
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doi: 10.57750/6v7b-8483
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draft: false
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journal: Computo
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pdf: ''
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authors: Thomas Ferté, Kalidou Ba, Dan Dutartre, Pierrick Legrand, Vianney Jouhet, Rodolphe Thiébaut, Xavier Hinaut and Boris P Hejblum
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date: 2025-06-27
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description: ''
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doi: 10.57750/arxn-6z34
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draft: false
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journal: Computo
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pdf: ''
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date: 2025-01-27
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description: >
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This document provides a full description of the Stochastic Individual-Based Models (IBMs) that can be implemented in the IBMPopSim package. A unified mathematical and simulation framework is given, with a detailed description of the simulation algorithm. Examples of applications for the package are also provided, showing the performance and flexibility of IBMPopSim.
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doi: 10.57750/sfxn-1t05
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draft: false
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journal: Computo
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pdf: ''
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authors: Félix Laplante and Christophe Ambroise
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date: 2024-12-13
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description: Scalable Spectral Clustering Based on Vector Quantization
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doi: 10.57750/1gr8-bk61
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draft: false
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journal: Computo
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pdf: ''
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authors: Herbert Susmann, Antoine Chambaz and Julie Josse
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date: 2024-07-18
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description: ''
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doi: 10.57750/edan-5f53
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draft: false
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journal: Computo
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pdf: ''
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authors: Juliette Legrand, François Pimont, Jean-Luc Dupuy and Thomas Opitz
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date: 2024-07-12
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description: ''
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doi: 10.57750/4y84-4t68
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draft: false
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journal: Computo
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pdf: ''
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authors: Liudmila Pishchagina, Guillem Rigaill and Vincent Runge
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date: 2024-07-12
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description: ''
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doi: 10.57750/9vvx-eq57
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draft: false
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journal: Computo
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pdf: ''
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Sources of error can arise from the workers' skills, but also from the intrinsic difficulty of the task.
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We introduce `peerannot`, a Python library for managing and learning from crowdsourced labels of image classification tasks.
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doi: 10.57750/qmaz-gr91
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draft: false
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journal: Computo
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pdf: ''
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date: 2024-03-11
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description: >
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This document provides a dimension-reduction strategy in order to improve the performance of importance sampling in high dimensions.
The package $\textsf{clayton}$ is designed to be intuitive, user-friendly, and efficient. It offers a wide range of copula models, including Archimedean, Elliptical, and Extreme. The package is implemented in pure $\textsf{Python}$, making it easy to install and use.
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