no code implementations • 21 Apr 2024 • João Gama, Rita P. Ribeiro, Saulo Mastelini, Narjes Davarid, Bruno Veloso
The system can present global explanations for the black box model and local explanations for why the black box model predicts a failure.
no code implementations • 2 Apr 2024 • Matias Molina, Rita P. Ribeiro, Bruno Veloso, João Gama
Illegal landfills are a critical issue due to their environmental, economic, and public health impacts.
no code implementations • 24 Jan 2024 • Alexandre Alcoforado, Thomas Palmeira Ferraz, Lucas Hideki Okamura, Israel Campos Fama, Arnold Moya Lavado, Bárbara Dias Bueno, Bruno Veloso, Anna Helena Reali Costa
But randomly sampling data to be annotated is often inefficient as it ignores the characteristics of the data and the specific needs of the model.
no code implementations • 8 Jun 2023 • Sepideh Pashami, Slawomir Nowaczyk, Yuantao Fan, Jakub Jakubowski, Nuno Paiva, Narjes Davari, Szymon Bobek, Samaneh Jamshidi, Hamid Sarmadi, Abdallah Alabdallah, Rita P. Ribeiro, Bruno Veloso, Moamar Sayed-Mouchaweh, Lala Rajaoarisoa, Grzegorz J. Nalepa, João Gama
We provide an overview of predictive maintenance tasks and accentuate the need and varying purposes for corresponding explanations.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
no code implementations • 10 Mar 2023 • Angelica Liguori, Luciano Caroprese, Marco Minici, Bruno Veloso, Francesco Spinnato, Mirco Nanni, Giuseppe Manco, Joao Gama
Point Processes provide a natural mathematical framework for modeling these sequences of events.
no code implementations • 12 Jul 2022 • Bruno Veloso, João Gama, Rita P. Ribeiro, Pedro M. Pereira
The paper describes the MetroPT data set, an outcome of a eXplainable Predictive Maintenance (XPM) project with an urban metro public transportation service in Porto, Portugal.