221 citations · 471 across the 24 of their papers we have counts for
24 papers
Contrastive learning for regression in multi-site brain age prediction
Carlo Alberto Barbano, Benoit Dufumier, Edouard Duchesnay +2
Building accurate Deep Learning (DL) models for brain age prediction is a very relevant topic in neuroimaging, as it could help better understand neurodegenerative disorders and fi…
Unbiased Supervised Contrastive Learning
Carlo Alberto Barbano, Benoit Dufumier, Enzo Tartaglione +2
Many datasets are biased, namely they contain easy-to-learn features that are highly correlated with the target class only in the dataset but not in the true underlying distributio…
Towards Efficient Capsule Networks
Riccardo Renzulli, Marco Grangetto
From the moment Neural Networks dominated the scene for image processing, the computational complexity needed to solve the targeted tasks skyrocketed: against such an unsustainable…
Disentangling private classes through regularization
Enzo Tartaglione, Francesca Gennari, Marco Grangetto
Deep learning models are nowadays broadly deployed to solve an incredibly large variety of tasks. However, little attention has been devoted to connected legal aspects. In 2016, th…
To update or not to update? Neurons at equilibrium in deep models
Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto
Recent advances in deep learning optimization showed that, with some a-posteriori information on fully-trained models, it is possible to match the same performance by simply traini…
Unsupervised Learning of Unbiased Visual Representations
Carlo Alberto Barbano, Enzo Tartaglione, Marco Grangetto
Deep neural networks often struggle to learn robust representations in the presence of dataset biases, leading to suboptimal generalization on unbiased datasets. This limitation ar…