221 citations · 507 across the 42 of their papers we have counts for
7 papers · 2 filters
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…
Packed-Ensembles for Efficient Uncertainty Estimation
Olivier Laurent, Adrien Lafage, Enzo Tartaglione +4
Deep Ensembles (DE) are a prominent approach for achieving excellent performance on key metrics such as accuracy, calibration, uncertainty estimation, and out-of-distribution detec…
Information Removal at the bottleneck in Deep Neural Networks
Enzo Tartaglione
Deep learning models are nowadays broadly deployed to solve an incredibly large variety of tasks. Commonly, leveraging over the availability of "big data", deep neural networks are…
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…
The rise of the lottery heroes: why zero-shot pruning is hard
Enzo Tartaglione
Recent advances in deep learning optimization showed that just a subset of parameters are really necessary to successfully train a model. Potentially, such a discovery has broad im…