Michele Casoni(University of Siena) When: Apr 13th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Mixture models A well known problem in the unsupervised learning framework is how to approximate an empirical distribution by a probability density function. A way for approaching it is provided by Mixture Models. In these probabilistic models, […]

Elia Giuseppe Ceroni (University of Siena) When: Apr 6th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Swim: a computational tool to unveiling crucial nodes in complex biological networks. SWItchMiner (SWIM) is a wizard-like software implementation of a procedure[1] capable to extract information contained in complex networks, developed by Paci et al.[2].Specifically, […]

Alessandra Romeo e Niccolò Fiorini (University of Siena) When: Mar 27th, 2022 – 3:00 – 4:00 PM Where: Google meet link

Pietro Bongini (University of Siena) When: Mar 9th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Modular multi-source prediction of drug side-effects with DruGNN Drug Side-Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes. Predicting the probability of side-effects, before their occurrence, is fundamental to […]

Gabriele Ciravegna (University of Siena) When: Mar 2nd, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Knowledge-driven Active Learning In the last few years, Deep Learning models have become increasingly popular. However, their deployment is still precluded in those contexts where the amount of supervised data is limited and manual labelling expensive. […]

Simone Marullo (University of Siena) When: Feb 16th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Optical Flow: history, state of the art and ongoing work The concept of optical flow, seen as a tool for motion detection and segmentation, has been of central importance in computer vision. Early algorithms are based […]

Veronica Lachi (University of Siena) When: Feb 9th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description A Mixed Statistical and Machine Learning approach for the Analysis of Multimodal Trail Making Test Data Eye-tracking can offer a novel clinical practice and a non-invasive tool to detect neuropathological syndromes. In this paper, we show […]

Caterina Graziani (University of Siena) When: Feb 2nd, 2022 – 11:45 – 12:30 AM Where: Google meet link Description Learning Representations over Dynamic Graphs Representation Learning over graph structured data has received significant attention recently due to its ubiquitous applicability. However, most advancements have been made in static graph settings while efforts for jointly learning […]

Giuseppe Alessio D’Inverno (University of Siena) When: Feb 2nd, 2022 – 11:00 – 11:45 AM Where: Google meet link Description The expressive power of Graph Neural Networks – A unifying point of view Graph Neural Networks (GNNs) are a wide class of connectionist models for graph processing. They perform an iterative message passing operation on […]

Lapo Faggi (University of Siena) When: Jan 19th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Learning invariant features from video streams: an optimal control approach Symmetries, invariances and conservation equations have always been an invaluable guide in Science to model natural phenomena through simple yet effective relations. For instance, in computer […]