31 citations · 31 across the 4 of their papers we have counts for
5 papers
OvAi Focus: AI-based Multi-class Segmentation of Functional Ovaries and Adnexal Masses in Gynecological Ultrasound
Niccolò Tallone, Francesca Salis, Pio Raffaele Fina +13
Ovarian cancer is the deadliest gynecological malignancy; accurate and objective segmentation of adnexal masses and functional ovaries in ultrasound (US) remains challenging due to…
Testing Transformer Learnability on the Arithmetic Sequence of Rooted Trees
Alessandro Breccia, Federica Gerace, Marco Lippi +2
We study whether a transformer network can learn the deterministic sequence of trees generated by the iterated prime factorization of the natural numbers. Each integer is mapped in…
A distributional simplicity bias in the learning dynamics of transformers
Riccardo Rende, Federica Gerace, Alessandro Laio +1
The remarkable capability of over-parameterised neural networks to generalise effectively has been explained by invoking a ``simplicity bias'': neural networks prevent overfitting…
Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks
Eszter Székely, Lorenzo Bardone, Federica Gerace +1
Neural networks excel at discovering statistical patterns in high-dimensional data sets. In practice, higher-order cumulants, which quantify the non-Gaussian correlations between t…
Mapping of attention mechanisms to a generalized Potts model
Riccardo Rende, Federica Gerace, Alessandro Laio +1
Transformers are neural networks that revolutionized natural language processing and machine learning. They process sequences of inputs, like words, using a mechanism called self-a…