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[Apr 29th 2020] LabMeeting: COVID-19 Italian and European pandemic: a SEIR model with undetected fraction and mobility-dependent transmission rate

Nicola Picchiotti Apr 29, 2020 – 11:00 AM Conference Meeting Description We propose a COVID-19 pandemic modelling, based on a SEIR compartmental framework, taking into account the heterogeneous fraction of undetected cases, the mobility variations along time and the adoption of personal protective measures. The model is experimentally validated across both Italian regions and several […]

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27 April 2020
 |  Category: Seminars

[Apr 22nd 2020] LabMeeting: A possible strategy to fight COVID-19:Interfering with spike glycoprotein trimerization.

Pietro Bongini (University of Florence) Apr 22, 2020 – 11:00 AM Conference Meeting Description The recent release of COVID-19 spike glycoprotein allows detailed analysis of the structural features that are required for stabilizing the infective form of its quaternary assembly. Trying to disassemble the trimeric structure of COVID-19 spike glycoprotein, we analyzed single protomer surfaces […]

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20 April 2020
 |  Category: Seminars
Interface of Monomer B (green) with Monomer A (red). The druggable pocket is highlighted in yellow

Research on Covid-19 spike protein

The spike glycoprotein of COVID-19 is fundamental in the life cicle of the virus, allowing virions to attach to host cell receptors. We analyzed the structure of this protein, which is composed of three monomers, searching for concave moieties located in the monomer-monomer interface regions. The presence of some druggable pockets in these locations suggests […]

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16 April 2020
 |  Category: Publications

[Apr 15 2020] LabMeeting: On Mutual Information Maximization for Representation Learning

Matteo Tiezzi (University of Siena) Apr 15, 2020 – 11:00 AM Conference Meeting Description Many recent methods for unsupervised or self-supervised representation learning train feature extractors by maximizing an estimate of the mutual information (MI) between different views of the data. This comes with several immediate problems. For example, MI is notoriously hard to estimate, […]

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14 April 2020
 |  Category: Seminars

A Variational Framework for Laws of Learning

Simplicity and elegance have always been incredibly useful criteria for the development of successful theories that describe natural phenomena. Variational methods frame this parsimony principles into precise mathematical statements. In this thesis we showed how we can formulate learning theories using calculus of variations. Despite the natural way in which learning problem can be formulated […]

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1 April 2020
 |  Category: PhD Theses

[Mar 4th 2020] LabMeeting: Human-Driven FOL Explanations of Deep Learning

Gabriele Ciravegna (University of Florence) Mar 4, 2020 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Deep neural networks are usually considered black-boxes due to their complex internal architecture, that cannot straightforwardly provide human-understandable explanations on how they behave. Indeed, Deep Learning is still viewed with skepticism in those real-world domains […]

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3 March 2020
 |  Category: Seminars

On the Integration of Logic and Learning

Giannini’s thesis A key point in the success of machine learning, and in particular deep learning, has been the availability of high-performance computing architectures allowing to process a large amount of data. However, this potentially prevents a wider application of machine learning in real world applications, where the collection of training data is often a […]

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13 February 2020
 |  Category: PhD Theses

[Feb 19th 2020] LabMeeting: Embedding of FRPN in CNN architecture

Alberto Rossi (University of Florence) Feb 19, 2020 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description This paper extends the fully recursive perceptron network (FRPN) model for vectorial inputs to include deep convolutional neural networks (CNNs) which can accept multi-dimensional inputs. A FRPN consists of a recursive layer, which, given a […]

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7 February 2020
 |  Category: Seminars

[Feb 19th 2020] LabMeeting: The Latent Topic Block Model for the Co-Clustering of Textual Interaction Data

Marco Corneli Feb 19, 2020 – 11:45 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description We consider textual interaction data involving two disjoint sets of individuals/objects. An example of such data is given by the reviews on web platforms (e.g. Amazon, TripAdvisor, etc.) where buyers comment on products/services they bought. We develop a […]

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 |  Category: Seminars