Search Results for author: Monica Bianchini

Found 9 papers, 0 papers with code

A Deep Learning Approach to the Prediction of Drug Side-Effects on Molecular Graphs

no code implementations30 Nov 2022 Pietro Bongini, Elisa Messori, Niccolò Pancino, Monica Bianchini

Predicting drug side-effects before they occur is a key task in keeping the number of drug-related hospitalizations low and to improve drug discovery processes.

Drug Discovery

Modular multi-source prediction of drug side-effects with DruGNN

no code implementations15 Feb 2022 Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolò Pancino, Pietro Liò

Drug Side-Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes.

Drug Discovery

A new perspective on the approximation capability of GNNs

no code implementations16 Jun 2021 Giuseppe Alessio D'Inverno, Monica Bianchini, Maria Lucia Sampoli, Franco Scarselli

Graph Neural Networks (GNNs) are a broad class of connectionist models for graph processing.

Molecular graph generation with Graph Neural Networks

no code implementations14 Dec 2020 Pietro Bongini, Monica Bianchini, Franco Scarselli

The use of graph neural networks maximizes the information in input at each generative step, which consists of the subgraph produced during the previous steps.

Drug Discovery Graph Generation +1

Weak Supervision for Generating Pixel-Level Annotations in Scene Text Segmentation

no code implementations19 Nov 2019 Simone Bonechi, Paolo Andreini, Monica Bianchini, Franco Scarselli

Providing pixel-level supervisions for scene text segmentation is inherently difficult and costly, so that only few small datasets are available for this task.

Text Segmentation

A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation

no code implementations29 Jul 2019 Paolo Andreini, Simone Bonechi, Monica Bianchini, Alessandro Mecocci, Franco Scarselli, Andrea Sodi

In this paper, we use Generative Adversarial Networks (GANs) for synthesizing high quality retinal images, along with the corresponding semantic label-maps, to be used instead of real images during the training process.

Image-to-Image Translation Retinal Vessel Segmentation

Modeling Taxi Drivers' Behaviour for the Next Destination Prediction

no code implementations21 Jul 2018 Alberto Rossi, Gianni Barlacchi, Monica Bianchini, Bruno Lepri

In this paper, we study how to model taxi drivers' behaviour and geographical information for an interesting and challenging task: the next destination prediction in a taxi journey.

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