Julian Gil-González

Aug 4, 2024 | mdpi.com | Jenniffer Carolina Triana-Martinez |Andrés Marino Álvarez-Meza |Julian Gil-González |Tom De Swaef

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Jul 15, 2024 | mdpi.com | Julián David Pastrana-Cortés |Julian Gil-González |Andrés Marino Álvarez-Meza |David Augusto Cárdenas-Peña

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

Apr 23, 2024 | preprints.org | Julián David Pastrana-Cortés |Julian Gil-González |Andrés Marino Álvarez-Meza |David Augusto Cárdenas-Peña

Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 19 April 2024 / Approved: 23 April 2024 / Online: 23 April 2024 (11:57:56 CEST) Pastrana-Cortés, J.D.; Gil-Gonzalez, J.; Álvarez-Meza, A.M.; Cárdenas-Peña, D.A.; Orozco-Gutiérrez, Á.A. Scalable and Interpretable Forecasting of Hydrological Time-Series based on Variational Gaussian Processes. Preprints 2024, 2024041492.

Mar 27, 2023 | mdpi.com | Andrés Marino Álvarez-Meza |Jenniffer Carolina Triana-Martinez |Julian Gil-González |Jose A. Fernandez-Gallego

Abstract:Supervised learning requires the accurate labeling of instances, usually provided by an expert. Crowdsourcing platforms offer a practical and cost-effective alternative for large datasets when individual annotation is impractical. In addition, these platforms gather labels from multiple labelers. Still, traditional multiple-annotator methods must account for the varying levels of expertise and the noise introduced by unreliable outputs, resulting in decreased performance.