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03/19/2023
Studying Limits of Explainability by Integrated Gradients for Gene Expression Models
Understanding the molecular processes that drive cellular life is a fund...
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10/08/2021
Graphs as Tools to Improve Deep Learning Methods
In recent years, deep neural networks (DNNs) have known an important ris...
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08/23/2021
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification
It is very common to face classification problems where the number of av...
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11/25/2020
Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs
Measuring the generalization performance of a Deep Neural Network (DNN) ...
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10/23/2020
Few-shot Learning for Decoding Brain Signals
Few-shot learning consists in addressing data-thrifty (inductive few-sho...
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07/08/2020
Predicting the Accuracy of a Few-Shot Classifier
In the context of few-shot learning, one cannot measure the generalizati...
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11/08/2019
Deep geometric knowledge distillation with graphs
In most cases deep learning architectures are trained disregarding the a...
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08/19/2019
Comparing linear structure-based and data-driven latent spatial representations for sequence prediction
Predicting the future of Graph-supported Time Series (GTS) is a key chal...
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05/01/2019
A Unified Deep Learning Formalism For Processing Graph Signals
Convolutional Neural Networks are very efficient at processing signals d...
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05/01/2019