439 citations · 2k across the 50 of their papers we have counts for
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Remote sensing image regression for heterogeneous change detection
Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser +1
Change detection in heterogeneous multitemporal satellite images is an emerging topic in remote sensing. In this paper we propose a framework, based on image regression, to perform…
The Deep Kernelized Autoencoder
Michael Kampffmeyer, Sigurd Løkse, Filippo M. Bianchi +2
Autoencoders learn data representations (codes) in such a way that the input is reproduced at the output of the network. However, it is not always clear what kind of properties of…
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders
Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen +2
Learning compressed representations of multivariate time series (MTS) facilitates data analysis in the presence of noise and redundant information, and for a large number of variat…
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples
Karl Øyvind Mikalsen, Cristina Soguero-Ruiz, Filippo Maria Bianchi +2
A large fraction of the electronic health records consists of clinical measurements collected over time, such as blood tests, which provide important information about the health s…
Reservoir computing approaches for representation and classification of multivariate time series
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse +1
Classification of multivariate time series (MTS) has been tackled with a large variety of methodologies and applied to a wide range of scenarios. Reservoir Computing (RC) provides…
Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs
Filippo Maria Bianchi, Lorenzo Livi, Alberto Ferrante +2
We tackle the problem of classifying Electrocardiography (ECG) signals with the aim of predicting the onset of Paroxysmal Atrial Fibrillation (PAF). Atrial fibrillation is the most…