681 citations · 772 across the 8 of their papers we have counts for
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cs.LG2021
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training
Anabel Gómez-Ríos, Julián Luengo, Francisco Herrera
Deep learning has outperformed other machine learning algorithms in a variety of tasks, and as a result, it is widely used. However, like other machine learning algorithms, deep le…
cs.LG2021★ 2 cited
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case
Natalia Díaz-Rodríguez, Alberto Lamas, Jules Sanchez +7
The latest Deep Learning (DL) models for detection and classification have achieved an unprecedented performance over classical machine learning algorithms. However, DL models are…