Vulgaris's Families Timeline

Vulgaris

Have a a look at the Technical report here! Our paper was recently accepted at VarDial 2020 Seventh Workshop on NLP for Similar Languages, Varieties and Dialects co-located with COLING 2020. Cite @misc{zugarini2020vulgaris, title={Vulgaris: Analysis of a Corpus for Middle-Age Varieties of Italian Language}, author={Andrea Zugarini and Matteo Tiezzi and Marco Maggini}, year={2020}, eprint={2010.05993}, archivePrefix={arXiv}, […]

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SAILenv

SAILenv is a Virtual Environment powered by Unity3D. It includes 3 pre-built scenes with full pixel-wise annotations. SAILenv is capable of generating frames at real-time speed, complete with pixel-wise annotations, optical flow and depth. SAILenv also comes with a Python API, designed to easily integrate with the most common learning frameworks available. Pixel-wise Annotations SAILenv […]

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Towards Laws of Visual Attention

PH.D. THESIS Author: Dario Zanca Date: March, 2019 Topics: Computational modeling of visual attention; Computer vision; Machine Learning. Abstract Visual attention is a crucial process for humans and foveated animals in general. The ability to select relevant locations in the visual field greatly simplifies the problem of vision. It allows a parsimonious management of the […]

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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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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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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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Neural Poetry: Learning to Generate Poems using Syllables

Andrea Zugarini (1,2), Stefano Melacci (2), Marco Maggini (2) (1) DINFO, University of Florence (2) DIISM, University of Siena Abstract Motivated by the recent progresses on machine learning-based models that learn artistic styles, in this paper we focus on the problem of poem generation. This is a challenging task in which the machine has to […]

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LYRICS: integrating Logic and Deep Learning

LINK TO THE PAPER¬†https://arxiv.org/abs/1903.07534 LINK TO THE REPO https://github.com/GiuseppeMarra/lyrics In spite of the amazing results obtained by deep learning in many applications, a real intelligent behavior of an agent acting in a complex environment is likely to require some kind of higher-level symbolic inference. Therefore, there is a clear need for the definition of a […]

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FixaTons: A collection of Human Fixations Datasets and Metrics for Scanpath Similarity

  Dario Zanca (1,2), Valeria Serchi (3), Pietro Piu (3), Francesca Rosini (3,4), Alessandra Rufa (3,4) (1) Department of Information Engineering, University of Florence, Florence, Italy (2) Department of Information Engineering and Mathematics, University of Siena, Siena, Italy (3) Eye-tracking and Visual Application Lab (EVALab), Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, […]

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Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow

Francesco Giannini (1), Vincenzo Laveglia (1,2), Alessandro Rossi (1,3), Dario Zanca (1,2), Andrea Zugarini (1) (1) DIISM, University of Siena, Siena, Italy (2) DINFO, University of Florence, Florence, Italy (3)¬†Fondazione Bruno Kessler, Trento, Italy Abstract An introduction to some Machine Learning tools within the most common development environments. It mainly focuses on practical problems, skipping […]

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