no code implementations • 25 Oct 2022 • Raffaele Marchesi, Nicolo Micheletti, Giuseppe Jurman, Venet Osmani
We show that our approach is better at both generating authentic data of the minority class and remaining within the original distribution of the real data.
no code implementations • 1 Oct 2019 • Gabriele Franch, Giuseppe Jurman, Luca Coviello, Marta Pendesini, Cesare Furlanello
The most challenging aspect of using this approach in the context of operational radar applications is to be able to perform a fast and accurate search for similar spatiotemporal precipitation patterns in a large archive of historical records.
no code implementations • 14 Sep 2019 • Nicole Bussola, Alessia Marcolini, Valerio Maggio, Giuseppe Jurman, Cesare Furlanello
We verify that accuracy scores may be inflated up to 41%, even if a well-designed 10x5 iterated cross-validation DAP is applied, unless all images from the same subject are kept together either in the internal training or validation splits.
no code implementations • 13 Sep 2019 • Andrea Gobbi, Marco Cristoforetti, Giuseppe Jurman, Cesare Furlanello
The historical weather data are then replaced with forecast values to predict LAI values at 10 day horizon on Europe.
no code implementations • 22 Nov 2017 • Valerio Maggio, Marco Chierici, Giuseppe Jurman, Cesare Furlanello
Neuroblastoma is a strongly heterogeneous cancer with very diverse clinical courses that may vary from spontaneous regression to fatal progression; an accurate patient's risk estimation at diagnosis is essential to design appropriate tumor treatment strategies.
no code implementations • 16 Oct 2017 • Giuseppe Jurman, Valerio Maggio, Diego Fioravanti, Ylenia Giarratano, Isotta Landi, Margherita Francescatto, Claudio Agostinelli, Marco Chierici, Manlio De Domenico, Cesare Furlanello
Convolutional Neural Networks (CNNs) are a popular deep learning architecture widely applied in different domains, in particular in classifying over images, for which the concept of convolution with a filter comes naturally.
no code implementations • 14 Sep 2017 • Nastaran Mohammadian Rad, Seyed Mostafa Kia, Calogero Zarbo, Twan van Laarhoven, Giuseppe Jurman, Paola Venuti, Elena Marchiori, Cesare Furlanello
Our results show that: 1) feature learning outperforms handcrafted features; 2) parameter transfer learning is beneficial in longitudinal settings; 3) using LSTM to learn the temporal dynamic of signals enhances the detection rate especially for skewed training data; 4) an ensemble of LSTMs provides more accurate and stable detectors.
no code implementations • 6 Sep 2017 • Diego Fioravanti, Ylenia Giarratano, Valerio Maggio, Claudio Agostinelli, Marco Chierici, Giuseppe Jurman, Cesare Furlanello
We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure.
no code implementations • 26 May 2017 • Marco Cristoforetti, Giuseppe Jurman, Andrea I. Nardelli, Cesare Furlanello
In several physical systems, important properties characterizing the system itself are theoretically related with specific degrees of freedom.
no code implementations • 5 Nov 2015 • Nastaran Mohammadian Rad, Andrea Bizzego, Seyed Mostafa Kia, Giuseppe Jurman, Paola Venuti, Cesare Furlanello
Autism Spectrum Disorders (ASDs) are often associated with specific atypical postural or motor behaviors, of which Stereotypical Motor Movements (SMMs) have a specific visibility.
no code implementations • 24 Oct 2013 • Tommaso Furlanello, Marco Cristoforetti, Cesare Furlanello, Giuseppe Jurman
The functional and structural representation of the brain as a complex network is marked by the fact that the comparison of noisy and intrinsically correlated high-dimensional structures between experimental conditions or groups shuns typical mass univariate methods.
1 code implementation • 29 Feb 2012 • Davide Albanese, Roberto Visintainer, Stefano Merler, Samantha Riccadonna, Giuseppe Jurman, Cesare Furlanello
mlpy is a Python Open Source Machine Learning library built on top of NumPy/SciPy and the GNU Scientific Libraries.